Energy storage system capacity configuration method and device and nonvolatile storage medium

Abstract

The invention discloses an energy storage system capacity configuration method and device and a nonvolatile storage medium. The method comprises the following steps: collecting wind and light output data corresponding to a target hydrogen production system in a preset time period; determining a wind-light simulation fluctuation rate based on the wind-light output data; determining charge data of an energy storage system corresponding to the target hydrogen production system according to the wind and light simulation fluctuation rate and a preset lifting and loading rate of the target hydrogen production system; determining a first configuration capacity of the energy storage system based on the charge data of the energy storage system; determining a second configuration capacity of the energy storage system according to a preset power demand; and determining the target configuration capacity of the energy storage system according to the first configuration capacity and the second configuration capacity. The technical problems that the actual configuration capacity is not accurate enough due to the fact that the capacity of the energy storage system for configuring the hydrogen production system at present is affected by various factors, resources are wasted due to too large configuration capacity, and risks easily exist due to too small configuration capacity are solved.

Description

Technical Field

[0001] The present invention relates to the field of new energy technologies, and in particular to a method and device for configuring the capacity of an energy storage system and a non-volatile storage medium. Background Art

[0002] In current wind and solar grid-connected projects, the capacity configuration of energy storage systems is mostly set based on local needs. The configuration is based on the stability of the system's hydrogen production, ignoring the ability of the current PEM hydrogen production system to adapt to power fluctuations, resulting in an increase in the actual configuration capacity, wasting resources and increasing investment costs; if the capacity is set too small, it may affect the operation of the hydrogen production system, which may lead to risks.

[0003] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0004] The embodiments of the present invention provide a method, device and non-volatile storage medium for configuring the capacity of an energy storage system, so as to at least solve the technical problem that the capacity of the energy storage system of the current hydrogen production system is affected by various factors, resulting in the actual configured capacity being inaccurate, the configured capacity being too large wasting resources, and the configured capacity being too small being prone to risks.

[0005] According to one aspect of an embodiment of the present invention, a method for configuring the capacity of an energy storage system is provided, including: collecting wind and solar power output data corresponding to a target hydrogen production system within a preset time period, wherein the wind and solar power output data represent data of wind power supply and photovoltaic power supply; determining a wind and solar power simulation fluctuation rate based on the wind and solar power output data, wherein the wind and solar power simulation fluctuation rate represents the rate of change of the output power of the simulated wind power supply and photovoltaic power supply; determining charge data of an energy storage system corresponding to the target hydrogen production system according to the wind and solar power simulation fluctuation rate and preset load and drop rates of the target hydrogen production system, wherein the preset load and drop rates represent the ability of the target hydrogen production system to adjust the input power; determining a first configuration capacity of the energy storage system based on the charge data of the energy storage system; determining a second configuration capacity of the energy storage system according to a preset power demand; and determining a target configuration capacity of the energy storage system according to the first configuration capacity and the second configuration capacity.

[0006] Optionally, based on the wind and solar power output data, determining the wind and solar power simulation fluctuation rate includes: interpolating the wind and solar power output data to obtain the wind and solar power simulation output data; and determining the wind and solar power simulation fluctuation rate based on the wind and solar power simulation output data.

[0007] Optionally, the wind and solar power output data are interpolated to obtain wind and solar power simulation output data, including: determining boundary conditions based on the wind and solar power output data; generating multiple random numbers based on the boundary conditions and a preset random number generation model; inserting the multiple random numbers into the wind and solar power output data to determine the wind and solar power simulation output data.

[0008] Optionally, the charge state data of the energy storage system corresponding to the target hydrogen production system is determined according to the simulated wind and solar fluctuation rate and the preset load and load rates of the hydrogen production system, including: determining the power tracking data of the target hydrogen production system according to the simulated wind and solar fluctuation rate and the preset load and load rates, wherein the power tracking data characterizes the ability of the target hydrogen production system to respond to power changes under the conditions of wind power supply and photovoltaic power supply; obtaining the power data to be smoothed of the energy storage system according to the power tracking data of the target hydrogen production system, wherein the power data to be smoothed characterizes the power fluctuation range that exceeds the power fluctuation that the target hydrogen production system can withstand and requires the intervention of the energy storage system; determining the charge data of the energy storage system according to the power to be smoothed of the energy storage system.

[0009] Optionally, based on the charge data of the energy storage system, determining the first configuration capacity of the energy storage system includes: performing segmented statistics based on the charge data of the energy storage system and multiple preset charge data segments to obtain the number of occurrences of each of the multiple charge data segments; determining the probability of occurrence of each of the multiple charge data segments based on the number of occurrences of each of the multiple charge data segments; and determining the first configuration capacity based on the charge data segments whose occurrence probabilities meet preset conditions among the multiple charge data segments.

[0010] Optionally, the preset power demand includes a power demand of a hydrogen purification system and a power demand of an auxiliary system.

[0011] Optionally, before determining the second configuration capacity of the energy storage system according to the preset power demand, the method includes: obtaining the input power of the hydrogen purification system and the input power of the auxiliary system; determining the power demand of the hydrogen purification system based on the input power of the hydrogen purification system and the preset purification time; determining the power demand of the auxiliary system based on the input power of the auxiliary system and the preset power consumption time of the auxiliary system; determining the preset power demand according to the power demand of the hydrogen purification system and the power demand of the auxiliary system.

[0012] According to another aspect of an embodiment of the present invention, a device for configuring the capacity of an energy storage system is also provided, including: a collection module for collecting wind and solar power output data corresponding to a target hydrogen production system within a preset time period, wherein the wind and solar power output data represent data of wind power supply and photovoltaic power supply; a first determination module for determining a wind and solar simulation fluctuation rate based on the wind and solar power output data, wherein the wind and solar simulation fluctuation rate represents the rate of change of the output power of the simulated wind power supply and photovoltaic power supply; a second determination module for determining the charge data of the energy storage system corresponding to the target hydrogen production system according to the wind and solar simulation fluctuation rate and a preset load and load rise and fall rate of the target hydrogen production system, wherein the preset load and load rise and fall rate represents the ability of the target hydrogen production system to adjust the input power; a third determination module for determining a first configuration capacity of the energy storage system based on the charge data of the energy storage system; a fourth determination module for determining a second configuration capacity of the energy storage system according to a preset power demand; a capacity determination module for determining a target configuration capacity of the energy storage system according to the first configuration capacity and the second configuration capacity.

[0013] According to another aspect of an embodiment of the present invention, a non-volatile storage medium is provided, the non-volatile storage medium including a stored program, wherein when the program is running, the device where the non-volatile storage medium is located is controlled to execute any one of the above-mentioned energy storage system capacity configuration methods.

[0014] According to another aspect of an embodiment of the present invention, a computer device is provided. The computer device includes a processor, and the processor is used to run a program. When the program is run, any one of the above energy storage system capacity configuration methods is executed.

[0015] According to yet another aspect of an embodiment of the present invention, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, any one of the above energy storage system capacity configuration methods is implemented.

[0016] In an embodiment of the present invention, a method for configuring the capacity of an energy storage system is adopted, by collecting wind and solar output data corresponding to a target hydrogen production system within a preset time period, wherein the wind and solar output data represent data of wind power supply and photovoltaic power supply; based on the wind and solar output data, a wind and solar simulation fluctuation rate is determined, wherein the wind and solar simulation fluctuation rate represents the rate of change of the output power of the simulated wind power supply and photovoltaic power supply; according to the wind and solar simulation fluctuation rate and the preset ramp rate of the target hydrogen production system, the charge data of the energy storage system corresponding to the target hydrogen production system is determined, wherein the preset ramp rate represents the ability of the target hydrogen production system to adjust the input power; based on the charge data of the energy storage system, a first configuration capacity of the energy storage system is determined; according to the preset power demand, a second configuration capacity of the energy storage system is determined; according to the first configuration capacity and the second configuration capacity, the target configuration capacity of the energy storage system is determined, so as to achieve the purpose of reasonably configuring the capacity of the energy storage system of the hydrogen production system, thereby achieving the technical effect of maintaining the stable operation of the hydrogen production system and reducing resource waste, and further solving the technical problem that the capacity of the energy storage system of the current hydrogen production system is affected by various factors, making the actual configuration capacity inaccurate, the configuration capacity is too large to waste resources, and too small to be prone to risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0018] Figure 1 A hardware structure block diagram of a computer terminal for implementing a method for configuring the capacity of an energy storage system is shown;

[0019] Figure 2 is a schematic diagram of a flow chart of a method for configuring energy storage system capacity according to an embodiment of the present invention;

[0020] Figure 3 It is a structural schematic diagram of a wind-solar hybrid off-grid hydrogen production system in a method for configuring the capacity of an energy storage system according to an optional embodiment of the present invention;

[0021] Figure 4 is a flow chart of a method for configuring the capacity of an energy storage system according to an optional embodiment of the present invention;

[0022] Figure 5 It is a structural block diagram of an energy storage system capacity configuration device provided according to an embodiment of the present invention. DETAILED DESCRIPTION

[0023] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0024] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0025] According to an embodiment of the present invention, a method embodiment of a method for configuring the capacity of an energy storage system is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0026] The method embodiment provided in the first embodiment of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Figure 1 The hardware structure block diagram of a computer terminal for implementing the energy storage system capacity configuration method is shown. Figure 1 As shown, the computer terminal 10 may include one or more (102a, 102b, ..., 102n are used to illustrate) processors (the processor may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 104 for storing data. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0027] It should be noted that the one or more processors and / or other data processing circuits described above may generally be referred to herein as "data processing circuits". The data processing circuits may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuit may be a single independent processing module, or may be incorporated in whole or in part into any of the other components in the computer terminal 10. As described in the embodiments of the present application, the data processing circuit acts as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0028] The memory 104 can be used to store software programs and modules of application software, such as program instructions / data storage devices corresponding to the energy storage system capacity configuration method in the embodiment of the present invention. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, the energy storage system capacity configuration method of the above-mentioned application is realized. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor, and these remote memories may be connected to the computer terminal 10 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0029] The display may be, for example, a touch screen liquid crystal display (LCD) that enables a user to interact with a user interface of the computer terminal 10 .

[0030] Figure 2 is a flow chart of a method for configuring energy storage system capacity according to an embodiment of the present invention. Figure 2 As shown, the method comprises the following steps:

[0031] Figure 3 is a structural schematic diagram of a wind-solar hybrid off-grid hydrogen production system in a method for configuring energy storage system capacity according to an optional embodiment of the present invention, such as Figure 3 As shown in the figure, the wind-solar hybrid off-grid hydrogen production system is a comprehensive energy system that combines wind power generation and photovoltaic power generation to produce hydrogen in an off-grid environment. It includes:

[0032] Wind power generation system: Wind turbine: converts wind energy into electrical energy. DC / AC converter (inverter): used to convert the direct current output of the wind turbine into alternating current for easy transmission and use.

[0033] Photovoltaic power generation system: Photovoltaic array: converts solar energy into electrical energy. AC / DC / AC converter: includes inverter and rectifier, used to convert the DC power output by the photovoltaic array into AC power, and then convert it into DC power suitable for electrolysis of water to produce hydrogen as needed.

[0034] Energy storage system: Energy storage battery: stores excess electricity when wind and solar power generation exceeds the demand of the hydrogen production system, and releases electricity when power generation is insufficient to smooth the power supply. DC / AC converter: connected to the energy storage battery, used for power conversion between the energy storage battery and the AC grid.

[0035] Hydrogen production system: Electrolyzer: Receives electricity and decomposes water into hydrogen and oxygen. Hydrogen production auxiliary system: Such as cooling system, compression system, safety control system, etc., to support the smooth progress of hydrogen production process. Transformer: Controls the voltage and current input to the electrolyzer to ensure its safe and stable operation.

[0036] It may also include a hydrogen purification system: a purification device such as pressure swing adsorption (PSA) or membrane separation technology, which is used to remove impurities generated during the hydrogen production process and improve the purity of the hydrogen.

[0037] The wind power generation and photovoltaic power generation systems in the system are connected to the hydrogen production system through the AC bus, and the energy storage system is also connected to the same bus, forming three main sources of power input. The operation of the hydrogen production system is affected by the real-time power supply, and the energy storage system plays a buffering role, regulating power supply and demand, and ensuring the continuous and stable operation of the hydrogen production system under the fluctuating energy supply environment.

[0038] Step S202 , collecting wind and solar power output data corresponding to the target hydrogen production system within a preset time period, wherein the wind and solar power output data represent data of wind power supply and photovoltaic power supply.

[0039] In this step, the wind and solar output data corresponding to the target hydrogen production system within the preset time period is collected, aiming to collect the output power information of wind power generation and photovoltaic power generation within a specific time range, which will be used for subsequent analysis and calculation to determine the reasonable configuration capacity of the energy storage system. It may be necessary to define a preset collection period, which is usually a one-year period, because wind and solar output is affected by various natural factors such as seasons and weather, and one year's data can fully cover various possible output conditions. The time period can be a continuous period of time, such as from January 1 to December 31, or it can be the average data of the past few years to reduce the impact of abnormal years. Within a certain time period, the real-time output power of wind farms and photovoltaic power stations is regularly recorded through sensors or data acquisition systems. These data may be stored in spreadsheets, databases or other forms, including wind power generation and photovoltaic power generation at each time point. The collected raw data can also be pre-processed, including: unifying the time interval of the data, such as adjusting it to collect once every 1 second or every 5 minutes, to maintain data consistency and facilitate subsequent analysis. Remove or correct abnormal values ​​caused by sensor failure, data transmission errors, etc.

[0040] Through the above steps, a data set reflecting the real-time changes in wind power supply and photovoltaic power supply can be obtained, which is used to guide the capacity configuration of the energy storage system, ensure that the hydrogen production system can operate stably when the wind and solar power output fluctuates, and optimize the economy and resource utilization efficiency of the overall system.

[0041] Step S204, determining a wind-solar simulation fluctuation rate based on the wind-solar output data, wherein the wind-solar simulation fluctuation rate represents a rate of change of the output power of the simulated wind power supply and photovoltaic power supply.

[0042] In this step, the wind-solar simulation fluctuation rate is determined based on the wind-solar output data to evaluate the speed at which the output power of wind power supply and photovoltaic power supply changes over time. Based on the wind-solar output data, for each data point, the power change amount compared with the previous time point is calculated and divided by the time interval to obtain the wind-solar output change rate at that time point.

[0043] Through the above steps, the wind and solar power output data is converted into wind and solar power simulation fluctuation rate, which can more intuitively understand the dynamic characteristics of renewable energy power generation, which is crucial for designing and optimizing the capacity configuration of energy storage systems. Reasonable wind and solar power simulation fluctuation rate analysis can help determine the charging and discharging requirements of the energy storage system on different time scales, thereby calculating the energy storage capacity that meets the system stability and economic requirements. At the same time, this also helps to evaluate the operating efficiency and reliability of the hydrogen production system, ensuring that the entire wind and solar complementary off-grid hydrogen production system can effectively cope with the volatility of wind and solar power output in actual operation.

[0044] Step S206, determining the charge data of the energy storage system corresponding to the target hydrogen production system according to the simulated wind-solar fluctuation rate and the preset ramp rate of the target hydrogen production system, wherein the preset ramp rate represents the ability of the target hydrogen production system to adjust the input power.

[0045] In this step, the state of charge (SOC) data of the energy storage system corresponding to the target hydrogen production system is determined according to the simulated wind and solar fluctuation rate and the preset ramp rate of the target hydrogen production system, in order to evaluate the charging and discharging requirements of the energy storage system to ensure the stable operation of the hydrogen production system in the face of renewable energy fluctuations. The hydrogen production system, whether it is an alkaline electrolyzer or a PEM electrolyzer, has its specific power adjustment capability, that is, the ramp rate. This refers to the ability of the hydrogen production system to safely and efficiently adjust its own power to adapt to changes in input power within a unit time. For example, the PEM hydrogen production system usually has a faster ramp rate and can better adapt to power fluctuations. Compare the simulated wind and solar fluctuation rate with the ramp rate of the target hydrogen production system to determine at which time points the hydrogen production system cannot follow the rapid changes in wind and solar output. The power fluctuations at these time points cannot be smoothed by the hydrogen production system itself, and the energy storage system needs to intervene to compensate. For power fluctuations that the hydrogen production system cannot respond to in time, calculate the power compensation that the energy storage system needs to provide, that is, the power to be smoothed. This involves calculating the charging and discharging requirements of the energy storage system based on the size and duration of the power fluctuations. Based on the power data to be smoothed, the state of charge of the energy storage system at different time points can be further analyzed and determined. SOC refers to the proportion of remaining energy in the energy storage system to the total energy, and is an important operating parameter. Through simulation and calculation, the SOC change trend of the energy storage system during charging and discharging operations to smooth out the fluctuations in wind and solar power output can be obtained on a specific time scale. Statistical analysis of the SOC data throughout the simulation cycle is performed to understand the fluctuation range, average value, and extreme cases of the state of charge of the energy storage system. This helps to evaluate the charge and discharge depth of the energy storage system, and whether there is sufficient capacity to cope with changes in electricity demand under the simulated fluctuation rate of wind and solar power.

[0046] Step S208: determining a first configuration capacity of the energy storage system based on the charge data of the energy storage system.

[0047] In this step, the first configuration capacity of the energy storage system is determined based on the state of charge (SOC) data of the energy storage system. This process mainly analyzes the distribution characteristics of the SOC data to ensure that the energy storage system can provide sufficient power smoothing capabilities when wind and solar power generation fluctuates, while avoiding resource waste caused by over-configuration. The state of charge data can be statistically analyzed, including but not limited to calculating the average value, standard deviation, minimum value, maximum value, and distribution of the entire data set of the SOC. This analysis helps to understand the fluctuation range and frequency of the state of charge of the energy storage system. The SOC data obtained by the statistical analysis are fitted with a normal distribution, which can more accurately describe the distribution characteristics of the SOC data and the range in which the SOC may fall at different time points. On the basis of the normal fitting, an SOC value at a high probability level is selected as a key reference point. For example, the maximum value of the SOC data range at a 95% probability level is selected, which ensures that in most cases (95% of the time), the energy storage system can maintain sufficient power to cope with the fluctuation of wind and solar power generation without running out of power. The first configuration capacity refers to the capacity that the energy storage system needs to configure at least in order to smooth the fluctuation of wind and solar output. This capacity should be sufficient to cover the power demand represented by the key SOC value, while taking into account the charging and discharging efficiency of the energy storage system.

[0048] Through the above steps, the first configuration capacity can be determined based on the charge state change trend of the energy storage system in the wind-solar hybrid off-grid hydrogen production system. The determination of this capacity not only takes into account the stability of the load demand of the hydrogen production system, but also fully evaluates the impact of the volatility of wind and solar power generation on the energy storage system, providing an important basis for ensuring the economy and reliability of the overall operation of the system. At the same time, considering the differences in load-raising and load-lowering performance of different technical routes of the hydrogen production system, this process can also adapt to the characteristics of the system more flexibly and achieve more accurate energy storage capacity planning.

[0049] Step S210: determining a second configuration capacity of the energy storage system according to a preset power demand.

[0050] In this step, determining the second configuration capacity of the energy storage system is another key link in the energy storage capacity configuration strategy of the wind-solar hybrid off-grid hydrogen production system, which aims to ensure that the hydrogen production system can continue to operate stably and meet its preset power demand during non-wind-solar power generation periods or when wind-solar power generation is insufficient. The second configuration capacity (S2) is usually associated with the power demand of the hydrogen production auxiliary system, the hydrogen purification system, and possible short-term wind and solar output reduction. The minimum preset power demand can be determined based on the operating parameters and design objectives of the hydrogen production system. This includes the normal operating power of hydrogen production auxiliary equipment (such as compressors and cooling systems), and the power required by the hydrogen purification system during the regeneration phase. In addition, the minimum power demand of the hydrogen production system when the wind and solar output is temporarily reduced should also be considered to maintain system stability. Evaluate the backup power demand of the hydrogen production auxiliary system in an emergency. Generally, the auxiliary system needs to be able to operate uninterruptedly for at least 0.5 hours, so part of the second configuration capacity should be the total power of the auxiliary system multiplied by 0.5 hours. The hydrogen purification system requires additional power during the regeneration phase, and this part of the power demand is usually the total power of the purification system multiplied by the time required for regeneration (for example, 5 hours). In the short period of time when the wind and solar output suddenly decreases, the energy storage system needs to supplement electricity to maintain the normal operation of the hydrogen production system. This part of the demand depends on the magnitude and duration of the reduction in wind and solar output, which can be estimated by analyzing historical data or based on a prediction model. The above requirements are summarized to obtain a preliminary calculation value of the second configuration capacity. The power demand fluctuations of the hydrogen production system under different working conditions can also be further analyzed to ensure that the second configuration capacity can cover all possible power demand peaks, including but not limited to high-load hydrogen production periods, instantaneous high power requirements when equipment starts / stops, etc. The determination of the second configuration capacity also needs to consider the overall stability of the system to ensure that the hydrogen production system can still rely on the power provided by the energy storage system to maintain operation and prevent production interruptions under extreme weather conditions or system failures. In summary, the determination of the second configuration capacity is based on the minimum power demand of the hydrogen production system and its auxiliary equipment, as well as the impact of wind and solar output fluctuations on system stability. Through precise calculation and comprehensive evaluation, it is possible to ensure that the role of the energy storage system in the wind and solar complementary off-grid hydrogen production system is maximized, while avoiding investment waste caused by over-configuration. This process reflects an in-depth understanding of the system's operating characteristics and the pursuit of a balance between the characteristics of renewable energy and the needs of the hydrogen production system.

[0051] Step S212: determining a target configuration capacity of the energy storage system according to the first configuration capacity and the second configuration capacity.

[0052] In this step, the first configuration capacity and the second configuration capacity can be added together and then divided by the discharge depth of the energy storage system to obtain the target configuration capacity, wherein the discharge depth reflects the proportion of the energy storage device that can be safely discharged to the remaining power, which is usually a key parameter that must be considered in the design of the energy storage system. After calculating the target configuration capacity, a certain system redundancy can also be considered to cope with unpredictable extreme situations or possible increase in electricity demand in the future. The target configuration capacity determined by the above steps can ensure the dynamic balance of electricity supply and demand, and also take into account the continuous operation requirements of key hydrogen production auxiliary equipment, thereby ensuring the stability and economy of the entire system.

[0053] Through the above steps, the purpose of reasonably configuring the capacity of the energy storage system of the hydrogen production system can be achieved, thereby achieving the technical effect of maintaining the stable operation of the hydrogen production system and reducing resource waste, and further solving the technical problem that the capacity of the energy storage system of the current hydrogen production system is affected by various factors, resulting in the actual configuration capacity being inaccurate, the configuration capacity being too large to waste resources, and the configuration capacity being too small to easily lead to risks.

[0054] As an optional embodiment, determining the wind-solar simulation fluctuation rate based on the wind-solar output data includes: interpolating the wind-solar output data to obtain the wind-solar simulation output data; and determining the wind-solar simulation fluctuation rate based on the wind-solar simulation output data.

[0055] Optionally, determining the wind-solar simulation fluctuation rate based on wind-solar output data helps to more accurately evaluate the dynamic characteristics of renewable energy generation. Obtaining wind-solar simulation output data can improve the time resolution of wind-solar output data and more truly reflect the volatility and randomness of wind-solar power generation. Wind-solar power generation output data is collected from historical records, which are usually recorded at time intervals of hours or longer. In order to improve the time resolution of the data, a random number method is used to interpolate between known data points to shorten the time interval to 1 second. When interpolating, it is necessary to ensure that the total output after interpolation is consistent with the total output of the original data. The fluctuation range and trend of the interpolated data conform to the statistical characteristics of the actual wind-solar output. For each interpolated time point, the change between the wind-solar output and the previous time point is calculated and divided by the time interval (1 second) to obtain the wind-solar simulation fluctuation rate. By analyzing the wind-solar simulation fluctuation rate, the power variation range that the energy storage system needs to smooth can be determined, thereby providing a basis for calculating the first configuration capacity of the energy storage system.

[0056] As an optional embodiment, interpolation processing is performed on wind and solar power output data to obtain wind and solar power simulation output data, including: determining boundary conditions based on the wind and solar power output data; generating multiple random numbers based on the boundary conditions and a preset random number generation model; inserting the multiple random numbers into the wind and solar power output data to determine the wind and solar power simulation output data.

[0057] Optionally, the wind and solar power output data are interpolated to obtain wind and solar power simulation output data. The boundary conditions can be determined first. The boundary conditions are used to constrain the data range and trend after interpolation processing to ensure that the interpolation results conform to the actual wind and solar power output mode. Based on the historical wind and solar power output data, the minimum output value, the maximum output value and the output change trend in each interpolation interval are determined. These conditions will guide the generation range and distribution of random numbers to maintain the authenticity and rationality of the data. For example, the output of wind power may be lower at night and higher during the day, and the interpolation process should reflect this diurnal change trend. Random numbers can be used to fill the gaps between the original data points and improve the temporal resolution of the data. A suitable random number generation model, such as Gaussian distribution, uniform distribution or other statistical models, can be selected to generate a series of random numbers according to the boundary conditions. These random numbers should be distributed within the range specified by the boundary conditions, and their distribution characteristics (mean, variance, etc.) should reflect the actual statistical characteristics of the wind and solar power output. The random numbers are inserted into the original wind and solar power output data to form wind and solar power simulation output data with higher temporal resolution. Between two adjacent points of the original data, linear interpolation or higher-order interpolation (such as spline interpolation) is performed based on the generated random numbers to obtain wind-solar simulation output data points with a time interval of 1 second. The interpolation process must ensure that the total output after interpolation is consistent with the total output of the original data to avoid distortion of the total energy. The volatility and trend of the interpolation results are consistent with the actual wind-solar output, which means that the amplitude and direction of changes between data points should reasonably reflect the real-time changes in wind-solar power generation. After completing the generation of wind-solar simulation output data, data verification can be performed to confirm whether the generated simulation data truly reflects the volatility and randomness of wind-solar power generation. Based on the verification results, it may be necessary to adjust the parameters of the random number generation model or redefine the boundary conditions to optimize the quality of the wind-solar simulation output data.

[0058] For example, the following formula can also be used for interpolation:

[0059] rand_factor=0.9+0.2*rand()

[0060]

[0061] Where rand_factor is the interpolation coefficient, To(i) is the initial time point, Po(i) is the initial output point, Tn(j) is the new time point, Pn(j) is the interpolation output point, and P(j) is the output point after interpolation.

[0062] As an optional embodiment, the charge state data of the energy storage system corresponding to the target hydrogen production system is determined according to the simulated wind and solar fluctuation rate and the preset load and load rates of the hydrogen production system, including: determining the power tracking data of the target hydrogen production system according to the simulated wind and solar fluctuation rate and the preset load and load rates, wherein the power tracking data characterizes the ability of the target hydrogen production system to respond to power changes under the conditions of wind power supply and photovoltaic power supply; obtaining the power data to be smoothed of the energy storage system according to the power tracking data of the target hydrogen production system, wherein the power data to be smoothed characterizes the power fluctuation range that exceeds the power fluctuation that the target hydrogen production system can withstand and requires the intervention of the energy storage system; determining the charge data of the energy storage system according to the power to be smoothed of the energy storage system.

[0063] Optionally, the state of charge (SOC) data of the energy storage system corresponding to the target hydrogen production system is determined according to the wind-solar simulation fluctuation rate and the preset load-down rate of the hydrogen production system to evaluate and optimize the operating stability of the hydrogen production system under renewable energy power supply conditions. Determining the power tracking data can evaluate the responsiveness of the target hydrogen production system under wind-solar power generation fluctuation conditions, that is, the range in which it can follow the power changes. Specifically, the wind-solar simulation fluctuation rate can be compared with the preset load-down rate of the hydrogen production system to determine the power change range to which the hydrogen production system can respond immediately. For each time point, if the wind-solar simulation fluctuation rate is less than or equal to the maximum load-up rate of the hydrogen production system or greater than the maximum load-down rate of the hydrogen production system, the hydrogen production system can follow the changes in wind-solar output, and this part of the data constitutes the power tracking data of the target hydrogen production system. If the wind-solar simulation fluctuation rate exceeds the load-down rate range of the hydrogen production system, it means that the hydrogen production system cannot respond to the wind-solar output changes immediately, and further analysis is required. The power data to be smoothed can be used to determine the power fluctuation range that exceeds the hydrogen production system's own tolerance, and this part of the fluctuation needs to be smoothed by the energy storage system. After comparing the simulated fluctuation rate of wind and solar power with the load-down and load-down rate of the hydrogen production system, mark all power change data points that the hydrogen production system cannot follow. For each data point that cannot be followed, calculate its power difference (i.e., the difference between the wind and solar power output and the actual load of the hydrogen production system). Summarize the power differences at all time points to obtain the total power data that the energy storage system needs to smooth during the entire simulation cycle, i.e., the power data to be smoothed. According to the power data to be smoothed, simulate the charging and discharging process of the energy storage system at each time point, and calculate the state of charge (SOC) change of the energy storage system. Consider the charging and discharging efficiency of the energy storage system, as well as the maximum and minimum state of charge limits, to ensure the rationality of the charge data. Perform statistical analysis on the calculated SOC data, including calculating the mean, standard deviation, and distribution characteristics of the SOC, to understand the dynamic range and stability of the state of charge. Based on the SOC data S1, ensure that under high probability conditions, the energy storage system can smooth out the fluctuations of wind and solar power generation, while avoiding cost waste caused by over-configuration.

[0064] For example, the power data to be smoothed can be determined by the following formula:

[0065] According to the wind and solar power output data points after the above interpolation, the simulated wind and solar power fluctuation rate is compared with the maximum load and load rate of the hydrogen production system to obtain the power tracking data of the hydrogen production system. The power fluctuation data that the hydrogen production system cannot follow is calculated, which is the power data to be smoothed by the energy storage system.

[0066]

[0067] Among them, PH(j) is the power data of the hydrogen production system, v(j) is the simulated fluctuation rate of wind and solar power, and vH is the load increase and load decrease rate of the hydrogen production system. In practice, the maximum load increase rate and maximum load decrease rate of the hydrogen production system can be set separately.

[0068] As an optional embodiment, determining a first configuration capacity of the energy storage system based on the charge data of the energy storage system includes: performing segmented statistics based on the charge data of the energy storage system and multiple preset charge data segments to obtain the number of occurrences of each of the multiple charge data segments; determining the probability of occurrence of each of the multiple charge data segments based on the number of occurrences of each of the multiple charge data segments; and determining the first configuration capacity based on the charge data segments whose probability of occurrence meets preset conditions in the multiple charge data segments.

[0069] Optionally, the first configuration capacity of the energy storage system is determined based on the state of charge (SOC) data of the energy storage system, aiming to find the economically optimal energy storage capacity while meeting the system stability and reliability requirements. The charge data can be segmented and counted, the purpose of which is to understand the distribution characteristics of the SOC data, identify the SOC range that appears frequently, and provide data support for the configuration capacity. The SOC data range can be divided into multiple preset segments, for example, the SOC range from 0% to 100% can be divided into 10% segments. For each segment, the number of occurrences of the SOC falling within the segment during the simulation process is recorded. This step helps identify the hot spots of the SOC data, that is, the range in which the SOC is most often in the system during operation. Determine the probability of occurrence of the charge data segment, and calculate the probability of occurrence of each segment based on the number of occurrences obtained by the charge data segment statistics. The probability of occurrence can be obtained by dividing the number of occurrences of each segment by the total number of data points. This probability data reflects the frequency of the SOC being in a specific range during system operation, which is crucial for subsequent capacity configuration decisions. Then, based on the probability of occurrence and system stability requirements, determine the capacity of an energy storage system that can smooth out power fluctuations without over-configuring. For example, select a charge data segment that meets the preset conditions as the basis for determining the first configuration capacity. Typically, the preset conditions take into account the stability and reliability requirements of the system. For example, segments that are distributed in the SOC data set under high probability (such as 95% probability) may be selected. Within the selected segment, find the difference between the highest SOC value and the lowest SOC value. This difference reflects the SOC variation range that the energy storage system needs to maintain when dealing with wind and solar fluctuations. Considering the discharge depth (D) of the energy storage system, that is, the proportion of the remaining power that the energy storage device can safely discharge, calculate the first configuration capacity.

[0070] According to the above energy storage system to be stabilized power data, the energy storage system SOC data is calculated, and statistics are performed in intervals to determine the normal fitting curve. The maximum value of the data range with a probability of 95% is selected as the configuration capacity S1 of the energy storage system. The specific formula is as follows:

[0071]

[0072] Among them, SOC(j) is the SOC data of the energy storage system.

[0073] As an optional embodiment, the preset power demand includes the power demand of the hydrogen purification system and the power demand of the auxiliary system.

[0074] Optionally, in the off-grid hydrogen production system with wind and solar hybrid, the preset power demand is a comprehensive consideration consisting of multiple subsystems, which is directly related to the overall operating efficiency and economy of the system. The preset power demand mainly includes the power demand of the hydrogen purification system and the power demand of the auxiliary system. Among them, some purification technologies (such as pressure swing adsorption PSA) need to be regenerated within a certain period to restore the activity of the adsorbent, and this process will require additional electricity. For example, a typical PSA purification system may need to be regenerated every 5 hours, and each regeneration process requires about 0.5 hours of electricity. This part of the demand must be fully considered when designing the system. Auxiliary systems refer to various systems that provide support for hydrogen production and purification processes, including but not limited to cooling systems, compression systems, control systems, etc. Although these systems are not directly involved in the generation of hydrogen, they are essential to maintaining the stability and safety of the entire hydrogen production process. In order to ensure the continuity and stability of the hydrogen production process, when the wind and solar output is reduced for a short time or the power supply is unstable, the auxiliary system needs to have a backup power supply to avoid unexpected shutdowns. For example, the cooling system and compression system may need to remain in operation for 0.5 hours to avoid overheating of the hydrogen production device or unstable hydrogen pressure.

[0075] Taking into account the above two parts of power demand, determining the second configuration capacity of the energy storage system is crucial to ensuring the stable operation of the hydrogen production system and improving the economic benefits of the entire system. The calculation of the second configuration capacity should include the power demand of the hydrogen purification system during normal operation and regeneration, as well as the backup power demand of the auxiliary system when the wind and solar power output is temporarily reduced. This not only ensures the continuity of the hydrogen production process and product quality, but also ensures that the system can effectively cope with power fluctuations and reduce unnecessary downtime risks under off-grid conditions.

[0076] As an optional embodiment, before determining the second configuration capacity of the energy storage system according to the preset power demand, it includes: obtaining the input power of the hydrogen purification system and the input power of the auxiliary system; determining the power demand of the hydrogen purification system based on the input power of the hydrogen purification system and the preset purification time; determining the power demand of the auxiliary system based on the input power of the auxiliary system and the preset power consumption time of the auxiliary system; determining the preset power demand according to the power demand of the hydrogen purification system and the power demand of the auxiliary system.

[0077] Optionally, the input power of the hydrogen purification system and the input power of the auxiliary system are obtained, and these data should reflect the power consumption under different operating modes (such as normal operation, regeneration, and standby). Based on the input power of the purification system and the preset duration of the purification process (such as the regeneration cycle), the total power demand of the purification system is calculated. In addition, the continuous power demand of the purification system in the non-regeneration stage can also be considered. The power demand of the auxiliary system can be determined based on the input power of the auxiliary system and the preset power consumption time of the auxiliary system, and the total power demand of the auxiliary system can be calculated. This part of the demand ensures that the auxiliary system can continue to operate when the wind and solar power output is insufficient to maintain the safety and stability of the hydrogen production process. The total power demand of the hydrogen purification system and the auxiliary system is summarized to obtain the preset power demand, which provides a calculation basis for the second configuration capacity of the energy storage system. For example, the power demand of the hydrogen purification system and the power demand of the auxiliary system are added to obtain the preset total power demand. Combined with the discharge depth of the energy storage system and the preset power demand, the second configuration capacity of the energy storage system is calculated.

[0078] Specifically, the partial energy storage system capacity S2 for hydrogen production load backup power includes the following: 1. 0.5h backup power for the auxiliary system; 2. 5h power consumption for hydrogen purification system regeneration; 3. When the wind and solar power output is temporarily reduced, the energy storage system compensates the power. The specific formula is as follows:

[0079]

[0080] Among them, Pf is the total power of the auxiliary system, Pc is the power of the hydrogen purification system, and test_factor is the short-term output reduction evaluation factor. When test_factor<1, it means that the output is reduced in the short term, and the energy storage system is needed to compensate for the output to ensure production.

[0081] Figure 4 is a flow chart of a method for configuring energy storage system capacity according to an optional embodiment of the present invention. Figure 4 As shown, an optional embodiment is provided, including:

[0082] For the part of smoothing the volatility of the power system, the following steps are included: 1. Obtain historical wind and solar power output data throughout the year, use the random number method to perform interpolation processing, and obtain the wind and solar power simulation output data for the whole year with a time interval of 1s; 2. Obtain the wind and solar power simulation fluctuation rate based on the wind and solar power simulation output data for the whole year, and compare the wind and solar power simulation fluctuation rate with the load and load rate of the hydrogen production system to obtain the power tracking data of the hydrogen production system; 3. According to the power tracking data of the hydrogen production system, calculate the power fluctuation data that the hydrogen production system cannot follow, which is the power data to be smoothed by the energy storage system; 4. According to the power to be smoothed by the energy storage system, calculate the SOC data of the energy storage system, divide it into intervals for statistics and make a normal fitting curve, and select the maximum value of the data range with a probability of 95% as the first configuration capacity S1 of the energy storage system.

[0083] The partial capacity S2 for the backup power of hydrogen production load includes the following: 1. 0.5h backup power of auxiliary system; 2. 5h power consumption of hydrogen purification system regeneration; 3. When the wind and solar power output is temporarily reduced, the energy storage system compensates the power. Based on the above content, the second configuration capacity S2 is determined.

[0084] The target configuration capacity is determined according to the first configuration capacity S1, the second configuration capacity S2 and the discharge depth.

[0085] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should know that the present invention is not limited by the described action sequence, because according to the present invention, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0086] Through the description of the above implementation methods, those skilled in the art can clearly understand that the energy storage system capacity configuration method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0087] According to an embodiment of the present invention, there is also provided an energy storage system capacity configuration device for implementing the above energy storage system capacity configuration method. Figure 5 is a structural block diagram of an energy storage system capacity configuration device provided according to an embodiment of the present invention, such as Figure 5 As shown, the energy storage system capacity configuration device includes: a collection module 502, a first determination module 504, a second determination module 506, a third determination module 508, a fourth determination module 510 and a capacity determination module 512. The energy storage system capacity configuration device is described below.

[0088] The collection module 502 is used to collect wind and solar power output data corresponding to the target hydrogen production system within a preset time period, wherein the wind and solar power output data represents the data of wind power supply and photovoltaic power supply.

[0089] The first determination module 504 is connected to the acquisition module 502, and is used to determine the wind-solar simulation fluctuation rate based on the wind-solar output data, wherein the wind-solar simulation fluctuation rate represents the rate of change of the output power of the simulated wind power supply and photovoltaic power supply.

[0090] The second determination module 506 is connected to the first determination module 504, and is used to determine the charge data of the energy storage system corresponding to the target hydrogen production system according to the wind-solar simulation fluctuation rate and the preset load and load rate of the target hydrogen production system, wherein the preset load and load rate represents the ability of the target hydrogen production system to adjust the input power.

[0091] The third determination module 508 is connected to the second determination module 506 and is used to determine the first configuration capacity of the energy storage system based on the charge data of the energy storage system.

[0092] The fourth determination module 510 is connected to the third determination module 508 and is used to determine the second configuration capacity of the energy storage system according to the preset power demand.

[0093] The capacity determination module 512 is connected to the fourth determination module 510 and is used to determine a target configuration capacity of the energy storage system according to the first configuration capacity and the second configuration capacity.

[0094] It should be noted that the acquisition module 502, the first determination module 504, the second determination module 506, the third determination module 508, the fourth determination module 510 and the capacity determination module 512 correspond to steps S202 to S212 in the embodiment, and the examples and application scenarios implemented by the multiple modules and the corresponding steps are the same, but are not limited to the contents disclosed in the above embodiment. It should be noted that the above modules, as part of the device, can be run in the computer terminal 10 provided in the embodiment.

[0095] An embodiment of the present invention may provide a computer device. Optionally, in this embodiment, the computer device may be located in at least one network device among multiple network devices of a computer network. The computer device includes a memory and a processor.

[0096] Among them, the memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the energy storage system capacity configuration method and device in the embodiment of the present invention. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, realizing the above-mentioned energy storage system capacity configuration method. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include a memory remotely arranged relative to the processor, and these remote memories can be connected to the computer terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0097] The processor can call the information and application programs stored in the memory through the transmission device to perform the following steps: collect the wind and solar power output data corresponding to the target hydrogen production system within a preset time period, wherein the wind and solar power output data represent the data of wind power supply and photovoltaic power supply; determine the wind and solar simulation fluctuation rate based on the wind and solar power output data, wherein the wind and solar simulation fluctuation rate represents the rate of change of the output power of the simulated wind power supply and photovoltaic power supply; determine the charge data of the energy storage system corresponding to the target hydrogen production system according to the wind and solar simulation fluctuation rate and the preset load and load rise and fall rates of the target hydrogen production system, wherein the preset load and load rise and fall rates represent the ability of the target hydrogen production system to adjust the input power; determine the first configuration capacity of the energy storage system based on the charge data of the energy storage system; determine the second configuration capacity of the energy storage system according to the preset power demand; determine the target configuration capacity of the energy storage system according to the first configuration capacity and the second configuration capacity.

[0098] Optionally, the processor may also execute the program code of the following steps: determining the wind-solar simulation fluctuation rate based on the wind-solar output data, including: interpolating the wind-solar output data to obtain the wind-solar simulation output data; determining the wind-solar simulation fluctuation rate based on the wind-solar simulation output data.

[0099] Optionally, the processor may also execute the program code of the following steps: interpolating the wind and solar power output data to obtain wind and solar simulation output data, including: determining boundary conditions based on the wind and solar power output data; generating multiple random numbers based on the boundary conditions and a preset random number generation model; inserting multiple random numbers into the wind and solar power output data to determine the wind and solar simulation output data.

[0100] Optionally, the processor may also execute program code for the following steps: determining the charge state data of the energy storage system corresponding to the target hydrogen production system according to the simulated wind and solar fluctuation rate and the preset load and load rates of the hydrogen production system, including: determining the power tracking data of the target hydrogen production system according to the simulated wind and solar fluctuation rate and the preset load and load rates, wherein the power tracking data represents the ability of the target hydrogen production system to respond to power changes under the conditions of wind power supply and photovoltaic power supply; obtaining the power data to be smoothed of the energy storage system according to the power tracking data of the target hydrogen production system, wherein the power data to be smoothed represents the power fluctuation range that exceeds the power fluctuation that the target hydrogen production system can withstand and requires the intervention of the energy storage system; determining the charge data of the energy storage system according to the power to be smoothed of the energy storage system.

[0101] Optionally, the processor may also execute program code for the following steps: determining a first configuration capacity of the energy storage system based on the charge data of the energy storage system, including: performing segmented statistics based on the charge data of the energy storage system and a plurality of preset charge data segments to obtain a corresponding number of occurrences of each of the plurality of charge data segments; determining a corresponding probability of occurrence of each of the plurality of charge data segments based on a corresponding number of occurrences of each of the plurality of charge data segments; and determining the first configuration capacity based on a charge data segment whose probability of occurrence meets preset conditions in the plurality of charge data segments.

[0102] Optionally, the processor may also execute program codes of the following steps: first, the preset power demand includes the power demand of the hydrogen purification system and the power demand of the auxiliary system.

[0103] Optionally, the processor may also execute program code for the following steps: before determining the second configuration capacity of the energy storage system according to a preset power demand, the steps include: obtaining the input power of the hydrogen purification system and the input power of the auxiliary system; determining the power demand of the hydrogen purification system based on the input power of the hydrogen purification system and a preset purification time; determining the power demand of the auxiliary system based on the input power of the auxiliary system and a preset power consumption time of the auxiliary system; and determining the preset power demand based on the power demand of the hydrogen purification system and the power demand of the auxiliary system.

[0104] By adopting the embodiment of the present invention, a method for configuring the capacity of an energy storage system is provided, by collecting wind and solar power output data corresponding to a target hydrogen production system within a preset time period, wherein the wind and solar power output data represent data of wind power supply and photovoltaic power supply; based on the wind and solar power output data, determining the wind and solar power simulation fluctuation rate, wherein the wind and solar power simulation fluctuation rate represents the rate of change of the output power of the simulated wind power supply and photovoltaic power supply; according to the wind and solar power simulation fluctuation rate and the preset ramp rate of the target hydrogen production system, determining the charge data of the energy storage system corresponding to the target hydrogen production system, wherein the preset ramp rate represents the ability of the target hydrogen production system to adjust the input power; based on the charge data of the energy storage system, determining a first configuration capacity of the energy storage system; according to the preset power demand, determining a second configuration capacity of the energy storage system; according to the first configuration capacity and the second configuration capacity, determining the target configuration capacity of the energy storage system, so as to achieve the purpose of reasonably configuring the capacity of the energy storage system of the hydrogen production system, thereby achieving the technical effect of maintaining the stable operation of the hydrogen production system and reducing resource waste, and further solving the technical problem that the capacity of the energy storage system of the current hydrogen production system is affected by various factors, resulting in the actual configuration capacity being inaccurate, the configuration capacity being too large to waste resources, and the configuration capacity being too small to easily have risks.

[0105] A person of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing the hardware related to the terminal device through a program, and the program can be stored in a non-volatile storage medium, and the storage medium may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0106] The embodiment of the present invention further provides a non-volatile storage medium. Optionally, in this embodiment, the non-volatile storage medium can be used to store the program code executed by the energy storage system capacity configuration method provided in the above embodiment.

[0107] Optionally, in this embodiment, the non-volatile storage medium may be located in any computer terminal in a computer terminal group in a computer network, or in any mobile terminal in a mobile terminal group.

[0108] Optionally, in this embodiment, the non-volatile storage medium is configured to store program codes for executing the following steps: collecting wind and solar power output data corresponding to the target hydrogen production system within a preset time period, wherein the wind and solar power output data represent data of wind power supply and photovoltaic power supply; determining a wind and solar power simulation fluctuation rate based on the wind and solar power output data, wherein the wind and solar power simulation fluctuation rate represents the rate of change of the output power of the simulated wind power supply and photovoltaic power supply; determining charge data of the energy storage system corresponding to the target hydrogen production system according to the wind and solar power simulation fluctuation rate and preset load and drop rates of the target hydrogen production system, wherein the preset load and drop rates represent the ability of the target hydrogen production system to adjust the input power; determining a first configuration capacity of the energy storage system based on the charge data of the energy storage system; determining a second configuration capacity of the energy storage system according to a preset power demand; determining a target configuration capacity of the energy storage system according to the first configuration capacity and the second configuration capacity.

[0109] Optionally, in this embodiment, the non-volatile storage medium is configured to store program codes for executing the following steps: determining a wind-solar simulation fluctuation rate based on wind-solar output data, including: interpolating the wind-solar output data to obtain wind-solar simulation output data; determining a wind-solar simulation fluctuation rate based on the wind-solar simulation output data.

[0110] Optionally, in this embodiment, the non-volatile storage medium is configured to store program codes for executing the following steps: interpolating wind and solar power output data to obtain wind and solar simulation output data, including: determining boundary conditions based on the wind and solar power output data; generating multiple random numbers based on the boundary conditions and a preset random number generation model; inserting multiple random numbers into the wind and solar power output data to determine the wind and solar simulation output data.

[0111] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for executing the following steps: determining the charge state data of the energy storage system corresponding to the target hydrogen production system according to the wind-solar simulation fluctuation rate and the preset load and load rates of the hydrogen production system, including: determining the power tracking data of the target hydrogen production system according to the wind-solar simulation fluctuation rate and the preset load and load rates, wherein the power tracking data characterizes the ability of the target hydrogen production system to respond to power changes under the conditions of wind power supply and photovoltaic power supply; obtaining the power data to be smoothed of the energy storage system according to the power tracking data of the target hydrogen production system, wherein the power data to be smoothed characterizes the power fluctuation range that exceeds the power fluctuation that the target hydrogen production system can withstand and requires the intervention of the energy storage system; determining the charge data of the energy storage system according to the power to be smoothed of the energy storage system.

[0112] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for executing the following steps: determining a first configuration capacity of the energy storage system based on the charge data of the energy storage system, including: performing segmented statistics based on the charge data of the energy storage system and a plurality of preset charge data segments to obtain a corresponding number of occurrences of each of the plurality of charge data segments; determining a corresponding probability of occurrence of each of the plurality of charge data segments based on a corresponding number of occurrences of each of the plurality of charge data segments; determining the first configuration capacity based on a charge data segment whose probability of occurrence meets preset conditions in the plurality of charge data segments.

[0113] Optionally, in this embodiment, the non-volatile storage medium is configured to store program codes for executing the following steps: the preset power demand includes the power demand of the hydrogen purification system and the power demand of the auxiliary system.

[0114] Optionally, in this embodiment, the non-volatile storage medium is configured to store program code for executing the following steps: before determining the second configuration capacity of the energy storage system according to a preset power demand, including: obtaining the input power of the hydrogen purification system and the input power of the auxiliary system; determining the power demand of the hydrogen purification system based on the input power of the hydrogen purification system and a preset purification time; determining the power demand of the auxiliary system based on the input power of the auxiliary system and a preset power consumption time of the auxiliary system; determining the preset power demand based on the power demand of the hydrogen purification system and the power demand of the auxiliary system.

[0115] An embodiment of the present invention also provides a computer program product, including a computer program. Optionally, in this embodiment, when the computer program is executed by a processor, it can achieve: collecting wind and solar power output data corresponding to a target hydrogen production system within a preset time period, wherein the wind and solar power output data represent data of wind power supply and photovoltaic power supply; determining a wind and solar simulation fluctuation rate based on the wind and solar power output data, wherein the wind and solar simulation fluctuation rate represents the rate of change of the output power of the simulated wind power supply and photovoltaic power supply; determining the charge data of an energy storage system corresponding to the target hydrogen production system according to the wind and solar simulation fluctuation rate and a preset load and load rise and fall rate of the target hydrogen production system, wherein the preset load and load rise and fall rate represents the ability of the target hydrogen production system to adjust the input power; determining a first configuration capacity of the energy storage system based on the charge data of the energy storage system; determining a second configuration capacity of the energy storage system according to a preset power demand; and determining a target configuration capacity of the energy storage system according to the first configuration capacity and the second configuration capacity.

[0116] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0117] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0118] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0119] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0120] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0121] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a non-volatile storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or 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 a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0122] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for configuring energy storage system capacity, characterized in that: include: Collecting wind and solar power output data corresponding to the target hydrogen production system within a preset time period, wherein the wind and solar power output data represents data of wind power supply and photovoltaic power supply; Based on the wind and solar power output data, determine the wind and solar power simulation fluctuation rate, wherein the wind and solar power simulation fluctuation rate represents the rate of change of the output power of the simulated wind power supply and photovoltaic power supply; Determine the charge data of the energy storage system corresponding to the target hydrogen production system according to the simulated wind-solar fluctuation rate and the preset load-down and load-down rates of the target hydrogen production system, wherein the preset load-down and load-down rates represent the ability of the target hydrogen production system to adjust the input power; Determining a first configuration capacity of the energy storage system based on the charge data of the energy storage system; Determining a second configuration capacity of the energy storage system according to a preset power demand; A target configuration capacity of the energy storage system is determined according to the first configuration capacity and the second configuration capacity.

2. The method according to claim 1, characterized in that The step of determining the wind / solar simulation fluctuation rate based on the wind / solar output data includes: Performing interpolation processing on the wind and solar power output data to obtain wind and solar power simulation output data; Based on the wind-solar simulation output data, the wind-solar simulation fluctuation rate is determined.

3. The method according to claim 2, characterized in that The interpolation processing of the wind and solar power output data to obtain wind and solar power simulation output data includes: Determining boundary conditions based on the wind and solar power output data; Based on the boundary conditions and a preset random number generation model, generate a plurality of random numbers; The multiple random numbers are inserted into the wind-solar power output data to determine the wind-solar simulation output data.

4. The method according to claim 1, characterized in that: Determining the state of charge data of the energy storage system corresponding to the target hydrogen production system according to the simulated wind-solar fluctuation rate and the preset load-down and load-down rates of the hydrogen production system includes: Determine the power tracking data of the target hydrogen production system according to the simulated wind-solar fluctuation rate and the preset load-down and load-down rate, wherein the power tracking data characterizes the ability of the target hydrogen production system to respond to power changes under the conditions of wind power supply and photovoltaic power supply; According to the power tracking data of the target hydrogen production system, the power data to be stabilized of the energy storage system is obtained, wherein the power data to be stabilized represents the power fluctuation range that exceeds the power fluctuation that the target hydrogen production system can bear and requires the intervention of the energy storage system; The charge data of the energy storage system is determined according to the power to be smoothed of the energy storage system.

5. The method according to claim 1, characterized in that The determining, based on the charge data of the energy storage system, a first configuration capacity of the energy storage system comprises: According to the charge data of the energy storage system and a plurality of preset charge data segments, segmented statistics are performed to obtain the number of occurrences corresponding to each of the plurality of charge data segments; Determining the occurrence probability of each of the plurality of charge data segments based on the number of occurrences of each of the plurality of charge data segments; The first configuration capacity is determined according to a charged data segment whose occurrence probability meets a preset condition among the multiple charged data segments.

6. The method according to any one of claims 1 to 5, characterized in that: The preset power demand includes the power demand of the hydrogen purification system and the power demand of the auxiliary system.

7. The method according to claim 6, characterized in that Before determining the second configuration capacity of the energy storage system according to the preset power demand, the method includes: Obtaining the input power of the hydrogen purification system and the input power of the auxiliary system; Determining the power demand of the hydrogen purification system based on the input power of the hydrogen purification system and a preset purification time; Determining the power demand of the auxiliary system based on the input power of the auxiliary system and the preset power consumption duration of the auxiliary system; The preset power requirement is determined according to the power requirement of the hydrogen purification system and the power requirement of the auxiliary system.

8. A device for configuring the capacity of an energy storage system, characterized in that: include: A collection module, used to collect wind and solar power output data corresponding to the target hydrogen production system within a preset period of time, wherein the wind and solar power output data represent data of wind power supply and photovoltaic power supply; A first determination module is used to determine a wind-solar simulation fluctuation rate based on the wind-solar output data, wherein the wind-solar simulation fluctuation rate represents a rate of change of output power of simulated wind power supply and photovoltaic power supply; A second determination module is used to determine the charge data of the energy storage system corresponding to the target hydrogen production system according to the wind-solar simulation fluctuation rate and the preset load-down and load-down rates of the target hydrogen production system, wherein the preset load-down and load-down rates represent the ability of the target hydrogen production system to adjust the input power; A third determination module, configured to determine a first configuration capacity of the energy storage system based on the charge data of the energy storage system; A fourth determination module, configured to determine a second configuration capacity of the energy storage system according to a preset power demand; A capacity determination module is used to determine a target configuration capacity of the energy storage system according to the first configuration capacity and the second configuration capacity.

9. A non-volatile storage medium, characterized in that: The non-volatile storage medium includes a stored program, wherein when the program is executed, the device where the non-volatile storage medium is located is controlled to execute the energy storage system capacity configuration method according to any one of claims 1 to 7.

10. A computer device, characterized in that: include: Memory and processor, The memory stores a computer program; The processor is used to execute the computer program stored in the memory, and when the computer program is running, the processor executes the energy storage system capacity configuration method according to any one of claims 1 to 7.

11. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the energy storage system capacity configuration method described in any one of claims 1 to 7 is implemented.

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