A distributed photovoltaic energy storage system and power control method thereof

Abstract

The present application provides a distributed photovoltaic energy storage system and its power control method, which determines the energy storage fitness of each photosensitive battery group through energy storage data; determines the impact load characteristics of each photosensitive battery group based on power load data, and then determines the impact load reduction of the photovoltaic energy storage station under transient overload based on all impact load characteristics, and determines the constraint cost of the charging power of the photovoltaic energy storage station under transient overload based on the impact load reduction and all energy storage fitness; determines the fluctuation smoothing coefficient of the charging power based on the fluctuation smoothing strategy, and then determines the load steady-state characteristics of each photosensitive battery group through the fluctuation smoothing coefficient and each energy storage fitness; determines the power smoothing amount of each photosensitive battery group when a load impact occurs based on each load steady-state characteristic and constraint cost, and balances and smoothes the photovoltaic energy storage station based on each power smoothing amount. Based on the above scheme, the load stability of the distributed photovoltaic network when a load impact occurs can be improved.

Description

Technical Field

[0001] The present application relates to the field of solar energy storage technology, and more specifically, to a distributed photovoltaic energy storage system and a power control method thereof. Background Art

[0002] Distributed photovoltaic energy storage networks use photovoltaic modules to convert solar energy into electricity. The efficiency of photovoltaic power generation is affected by factors such as light intensity, photovoltaic panel angle and temperature. Distributed photovoltaic energy storage networks are designed to solve stability problems in traditional power systems, improve the utilization efficiency of photovoltaic power generation, and achieve reliable energy supply through effective energy storage and power regulation. By continuously optimizing distributed photovoltaic energy storage networks, distributed photovoltaic energy storage networks can better meet modern energy needs and achieve sustainable development. The main challenges facing photovoltaic energy storage systems are power fluctuations and load shocks.

[0003] Photovoltaic power generation is random, intermittent, and volatile. With the increase in installed capacity of photovoltaic power generation, grid voltage, power quality, and operation control are increasingly affected, especially when a load shock occurs in a distributed photovoltaic network. The load shock will cause a large sag and overshoot in the output voltage, and even lead to instability in the distributed photovoltaic energy storage network, which may pose a threat to the safe and stable operation of the power grid. The volatility and load shock of photovoltaic power generation can be effectively dealt with by balancing and smoothing the load power supply, thereby improving the load steady-state characteristics of the distributed photovoltaic network. Therefore, how to achieve balanced and smooth load power supply in photovoltaic energy storage stations can improve the load stability of distributed photovoltaic networks when load shocks occur. Summary of the invention

[0004] The present application provides a distributed photovoltaic energy storage system and a power control method thereof, which can achieve balanced and smooth control of load power supply in a photovoltaic energy storage station, thereby improving the load stability of the distributed photovoltaic network when a load shock occurs.

[0005] In a first aspect, the present application provides a distributed photovoltaic energy storage power control method, comprising:

[0006] Obtain the energy storage records and power load records of each photosensitive battery group in the photovoltaic energy storage station from the distributed photovoltaic network, and then obtain the energy storage data and power load data;

[0007] Determine the energy storage adaptability of each photosensitive battery group of the photovoltaic energy storage station under load steady state according to the steady-state characteristics of the load power in the photovoltaic energy storage station and the power gradient of the energy storage data;

[0008] Determine the impact load reduction amount of the photovoltaic energy storage station under transient overload according to the impact load characteristics of each photosensitive battery group in the power load data, and determine the constraint cost of the charging power of the photovoltaic energy storage station under transient overload through the impact load reduction amount and all energy storage adaptability;

[0009] Through the load power fluctuation smoothing strategy in the photovoltaic energy storage station and the adaptability of each energy storage, the load fluctuation of each photosensitive battery group in the photovoltaic energy storage station is calibrated, and then the load steady-state characteristics of each photosensitive battery group are obtained;

[0010] The power smoothing amount of each photosensitive battery group when a load impact occurs in the photovoltaic energy storage station is determined according to the steady-state characteristics of each load and the constraint cost, and the load power supply power of the photovoltaic energy storage station is balanced and smoothed based on each power smoothing amount.

[0011] In some embodiments, determining the energy storage adaptability of each photosensitive battery group of the photovoltaic energy storage station under load steady state according to the steady-state characteristics of the load power in the photovoltaic energy storage station and the power gradient of the energy storage data specifically includes:

[0012] Extracting a steady-state interval of load power from the power load data according to the steady-state characteristics of load power in the photovoltaic energy storage station;

[0013] For each photosensitive battery group of the photovoltaic energy storage station under load steady state, a charging power curve of the photosensitive battery group is determined according to the power gradient of the energy storage record of the photosensitive battery group in the energy storage data;

[0014] Intercepting the steady-state energy storage curve of the photosensitive battery pack in the steady-state load state from the charging power curve through the steady-state interval;

[0015] The energy storage adaptability of the photosensitive battery group of the photovoltaic energy storage station under the load steady state is determined according to the steady-state energy storage curve, and then the energy storage adaptability of each photosensitive battery group of the photovoltaic energy storage station under the load steady state is obtained.

[0016] In some embodiments, determining the impact load reduction amount of the photovoltaic energy storage station under transient overload according to the impact load characteristics of each photosensitive battery group in the power load data specifically includes:

[0017] For each photosensitive battery group in the photovoltaic energy storage station, obtaining a power load record of the photosensitive battery in the power load data;

[0018] Determine the impact load of the photosensitive battery group each time a load impact occurs in the photovoltaic energy storage station according to the power load record;

[0019] Determine the impact load characteristics of the photosensitive battery group when the photovoltaic energy storage station has a load impact through all the impact load amounts, and then obtain the impact load characteristics of each photosensitive battery group when the photovoltaic energy storage station has a load impact;

[0020] The impact load reduction of the photovoltaic energy storage station under transient overload is determined by all impact load characteristics.

[0021] In some embodiments, determining the impact load reduction amount of the photovoltaic energy storage station under transient overload based on all impact load characteristics specifically includes:

[0022] For each photosensitive battery group in the photovoltaic energy storage station, determine all overload impact states of the photosensitive battery group;

[0023] Determine the load difference value of the photosensitive battery group under each overload impact state according to the impact load characteristics of the photosensitive battery group;

[0024] Determine the load reduction value of the photosensitive battery group under transient overload according to all load difference values, and then obtain the load reduction value of each photosensitive battery group under transient overload in the photovoltaic energy storage station;

[0025] The impact load reduction of the photovoltaic energy storage station under transient overload is determined by all impact load reductions.

[0026] In some embodiments, determining the constraint cost of the charging power of the photovoltaic energy storage station under transient overload by using the impact load reduction amount and all energy storage adaptability specifically includes:

[0027] Obtain the load threshold of the photovoltaic energy storage station;

[0028] Determining a transient overload amount of the photovoltaic energy storage station by using the impact load reduction amount and the load threshold;

[0029] Determine the energy storage dispatching amount of the photovoltaic energy storage station based on all energy storage adaptability;

[0030] The constraint cost of the charging power of the photovoltaic energy storage station under transient overload is determined by the energy storage scheduling amount and the transient overload amount.

[0031] In some embodiments, the load fluctuation of each photosensitive battery group in the photovoltaic energy storage station is calibrated by the load power fluctuation smoothing strategy and each energy storage adaptability in the photovoltaic energy storage station, and the load steady-state characteristics of each photosensitive battery group are obtained, which specifically include:

[0032] Obtain the load power fluctuation smoothing strategy in the photovoltaic energy storage station;

[0033] Determining a fluctuation smoothing coefficient of charging power in the photovoltaic energy storage station according to the fluctuation smoothing strategy and the fluctuation characteristics of charging power in the photovoltaic energy storage station;

[0034] The fluctuation of the load of each photosensitive battery group in the photovoltaic energy storage station is calibrated by the fluctuation smoothing coefficient and each energy storage adaptability, so as to obtain the load steady-state characteristics of each photosensitive battery group.

[0035] In some embodiments, the load power supply power of the photovoltaic energy storage station is balanced and smoothed based on each power smoothing amount. When a load shock occurs, each power smoothing amount is used as the discharge power of the corresponding photosensitive battery group in the photovoltaic energy storage station to complete the balanced smoothing of the load power supply power in the photovoltaic energy storage station.

[0036] In a second aspect, the present application provides a distributed photovoltaic energy storage system, including a charging power control unit, wherein the charging power control unit includes:

[0037] An acquisition module is used to acquire energy storage records and power load records of each photosensitive battery group in a photovoltaic energy storage station from a distributed photovoltaic network, thereby obtaining energy storage data and power load data;

[0038] A processing module, used to determine the energy storage adaptability of each photosensitive battery group of the photovoltaic energy storage station under load steady state according to the steady-state characteristics of the load power in the photovoltaic energy storage station and the power gradient of the energy storage data;

[0039] The processing module is also used to determine the impact load reduction amount of the photovoltaic energy storage station under transient overload according to the impact load characteristics of each photosensitive battery group in the power load data, and determine the constraint cost of the charging power of the photovoltaic energy storage station under transient overload through the impact load reduction amount and all energy storage adaptability;

[0040] The processing module is also used to calibrate the load fluctuation of each photosensitive battery group in the photovoltaic energy storage station through the load power fluctuation smoothing strategy in the photovoltaic energy storage station and each energy storage adaptability, so as to obtain the load steady-state characteristics of each photosensitive battery group;

[0041] The execution module is used to determine the power smoothing amount of each photosensitive battery group when a load impact occurs in the photovoltaic energy storage station according to the steady-state characteristics of each load and the constraint cost, and balance and smooth the load power supply power of the photovoltaic energy storage station based on each power smoothing amount.

[0042] In a third aspect, the present application provides a computer device, comprising a memory and a processor, wherein the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the above-mentioned distributed photovoltaic energy storage power control method.

[0043] In a fourth aspect, the present application provides a computer-readable storage medium, in which instructions or codes are stored. When the instructions or codes are run on a computer, the computer implements the above-mentioned distributed photovoltaic energy storage power control method when executed.

[0044] The technical solution provided by the embodiments disclosed in this application has the following beneficial effects:

[0045] In a distributed photovoltaic energy storage system and power control method provided by the present application, energy storage records and power load records of each photosensitive battery group in a photovoltaic energy storage station are obtained from a distributed photovoltaic network, thereby obtaining energy storage data and power load data; the energy storage fitness of each photosensitive battery group in the photovoltaic energy storage station under load steady state is determined according to the steady-state characteristics of the load power in the photovoltaic energy storage station and the power gradient of the energy storage data; the impact load reduction amount of the photovoltaic energy storage station under transient overload is determined according to the impact load characteristics of each photosensitive battery group in the power load data, and the constraint cost of the charging power of the photovoltaic energy storage station under transient overload is determined by the impact load reduction amount and all energy storage fitnesses; the load fluctuation of each photosensitive battery group in the photovoltaic energy storage station is calibrated by the load power fluctuation smoothing strategy in the photovoltaic energy storage station and each energy storage fitness, thereby obtaining the load steady-state characteristics of each photosensitive battery group; the power smoothing amount of each photosensitive battery group when a load impact occurs in the photovoltaic energy storage station is determined according to each load steady-state characteristic and the constraint cost, and the load power supply power of the photovoltaic energy storage station is balanced and smoothed based on each power smoothing amount.

[0046] It can be seen that in this application, the power smoothing amount of each photosensitive battery group when a load impact occurs in the photovoltaic energy storage station is determined according to the steady-state characteristics of each load and the constraint cost, and the load power supply power of the photovoltaic energy storage station is balanced and smoothed based on each power smoothing amount; firstly, determining the energy storage adaptability can evaluate the energy storage capacity of different battery groups under long-term stable load conditions, thereby optimizing the configuration of energy storage resources, facilitating the subsequent balanced smoothing of load power supply power, ensuring that the photovoltaic energy storage system can effectively respond to power fluctuations under load steady state, and improving the stability of distributed photovoltaic networks under load impact; secondly, the impact load reduction under transient overload can accurately evaluate the performance of each battery group during load impact and the load changes that need to be borne, and can identify potential deficiencies in the energy storage system, which is convenient for formulating effective responses to load impacts. For the measures, the energy storage scheduling strategy can be optimized by calculating the constraint cost to ensure that the energy storage system can operate stably under transient overload conditions. By reasonably allocating energy storage resources, the impact of power fluctuations can be reduced and the load steady-state characteristics of the system can be enhanced. Finally, by determining the power smoothing amount according to the load steady-state characteristics and the constraint cost, the charging power can be reasonably allocated when a load shock occurs, and balanced power smoothing can be performed when a load shock occurs in the energy storage system, reducing the impact of power fluctuations on the energy storage system. Balanced smoothing can enable the energy storage system to absorb and release power more effectively, thereby improving the stability of the distributed photovoltaic network when a load shock occurs. In summary, based on the above scheme, the balanced smoothing of the load power supply in the photovoltaic energy storage station can be achieved, thereby improving the load stability of the distributed photovoltaic network when a load shock occurs. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0048] Figure 1 is an exemplary flow chart of a distributed photovoltaic energy storage power control method according to some embodiments of the present application;

[0049] Figure 2 is a schematic diagram of a process for determining the impact load reduction amount according to some embodiments of the present application;

[0050] Figure 3 is a schematic diagram of a process for determining a steady-state characteristic of a load according to some embodiments of the present application;

[0051] Figure 4 is a schematic diagram of exemplary hardware and / or software of a charging power control unit according to some embodiments of the present application;

[0052] Figure 5 It is a structural schematic diagram of a computer device for implementing a distributed photovoltaic energy storage power control method according to some embodiments of the present application. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0054] The embodiment of the present application provides a distributed photovoltaic energy storage system and its power control method, the core of which is to determine the energy storage fitness of each photosensitive battery group through energy storage data; determine the impact load characteristics of each photosensitive battery group based on power load data, and then determine the impact load reduction of the photovoltaic energy storage station under transient overload based on all impact load characteristics, and determine the constraint cost of the charging power of the photovoltaic energy storage station under transient overload based on the impact load reduction and all energy storage fitness; determine the fluctuation smoothing coefficient of the charging power based on the fluctuation smoothing strategy, and then determine the load steady-state characteristics of each photosensitive battery group through the fluctuation smoothing coefficient and each energy storage fitness; determine the power smoothing amount of each photosensitive battery group when a load shock occurs to the photovoltaic energy storage station based on each load steady-state characteristic and constraint cost, and balance and smooth the load power supply power of the photovoltaic energy storage station based on each power smoothing amount. Based on the above scheme, the load stability of the distributed photovoltaic network when a load shock occurs can be improved.

[0055] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods. Figure 1 , which is an exemplary flow chart of a distributed photovoltaic energy storage power control method according to some embodiments of the present application, and the distributed photovoltaic energy storage power control method mainly includes the following steps:

[0056] In step 101, energy storage records and power load records of each photosensitive battery group in a photovoltaic energy storage station are obtained from a distributed photovoltaic network, thereby obtaining energy storage data and power load data.

[0057] It should be noted that in the present application, the energy storage data is a data set of energy storage records of each photosensitive battery group in the photovoltaic energy storage station, and the energy storage record records the changes in the power of each photosensitive battery group; the power load data is a data set of power load records of each photosensitive battery group in the photovoltaic energy storage station, and the power load record records the power usage of the load equipment.

[0058] In specific implementation, the energy storage records and power load records of each photosensitive battery group in the photovoltaic energy storage station within a preset time period (the default is the most recent 1 month) are obtained from the distributed photovoltaic network. The collection of all energy storage records can be used as energy storage data, and the collection of all power load records can be used as power load data. In this application, the energy storage information and power load information of each photosensitive battery group are collected at a frequency of once per second. The energy storage information includes charging power and discharging power, and the power load information includes load status, instantaneous power and average power. The load status includes normal state and overload state.

[0059] In step 102, the energy storage adaptability of each photosensitive battery group of the photovoltaic energy storage station under the load steady state is determined according to the steady-state characteristics of the load power in the photovoltaic energy storage station and the power gradient of the energy storage data.

[0060] It should be noted that, in the present application, the steady-state characteristics refer to the power characteristics when the load power in the photovoltaic energy storage station remains in a relatively constant state. The relatively constant state means that the power fluctuation is within the range of a preset fluctuation threshold, and the fluctuation threshold can be obtained in the distributed photovoltaic network; in specific implementation, the preset fluctuation threshold in the distributed photovoltaic network can be used as the steady-state characteristics of the load power in the photovoltaic energy storage station. In other embodiments, other methods can also be used to determine the steady-state characteristics of the load power in the photovoltaic energy storage station, which will not be repeated here.

[0061] In some embodiments, the following steps may be used to determine the energy storage adaptability of each photosensitive battery group in the photovoltaic energy storage station under load steady state according to the steady-state characteristics of the load power in the photovoltaic energy storage station and the power gradient of the energy storage data:

[0062] Extracting a steady-state interval of load power from the power load data according to the steady-state characteristics of load power in the photovoltaic energy storage station;

[0063] For each photosensitive battery group of the photovoltaic energy storage station under load steady state, a charging power curve of the photosensitive battery group is determined according to the power gradient of the energy storage record of the photosensitive battery group in the energy storage data;

[0064] Intercepting the steady-state energy storage curve of the photosensitive battery pack in the steady-state load state from the charging power curve through the steady-state interval;

[0065] The energy storage adaptability of the photosensitive battery group of the photovoltaic energy storage station under the load steady state is determined according to the steady-state energy storage curve, and then the energy storage adaptability of each photosensitive battery group of the photovoltaic energy storage station under the load steady state is obtained.

[0066] It should be noted that in the present application, energy storage adaptability reflects the adaptability and stability of the photosensitive battery group to load demand; the steady-state interval refers to the time interval in which the load power remains relatively constant; the power gradient refers to the rate of change of the charging power in the photosensitive battery group; the charging power curve represents the curve of the change process of the charging power in the photosensitive battery group; the steady-state energy storage curve is a curve that reflects the power performance of the photosensitive battery group under stable load conditions.

[0067] In specific implementation, first, the sum of the average powers of all energy storage information collected each time in the power load data is taken as the load power value at the corresponding collection moment, and the difference between the load power values ​​at adjacent collection moments is taken as the load change value. The interval composed of the collection moments where the load change value is within the steady-state characteristics of the load power in the photovoltaic energy storage station can be taken as the steady-state interval of the load power; secondly, for each photosensitive battery group in the photovoltaic energy storage station, the difference in the charging power of the photosensitive battery group at adjacent collection moments in the corresponding energy storage record in the energy storage data can be taken as the power gradient of the next moment in the adjacent collection moments, and the collection of all power gradients can be taken as the power gradient of the photosensitive battery group. Power gradient, taking the collection time as the horizontal axis and the power gradient as the vertical axis, a Cartesian coordinate system is established, and all power gradients in the power gradient are mapped to the Cartesian coordinate system. The curve connected in sequence according to the collection time can be used as the charging power curve; then, the part of the charging power curve in the steady-state interval at the collection time can be intercepted as the steady-state energy storage curve; finally, the difference between the mean of all maximum values ​​and the mean of all minimum values ​​in the steady-state energy storage curve can be used as the energy storage fitness of the photosensitive battery group of the photovoltaic energy storage station under the steady-state load. The energy storage fitness of each photosensitive battery group of the photovoltaic energy storage station under the steady-state load can be obtained in the above manner.

[0068] It should be noted that determining the energy storage adaptability can quantify the actual adaptability of the photosensitive battery group and ensure that the photosensitive battery group can operate effectively under steady-state load, thereby providing a basis to support the steady-state optimization of the photosensitive battery group and improve the performance and efficiency of the photosensitive battery group, thereby determining the energy storage adaptability of each photosensitive battery group of the photovoltaic energy storage station under steady-state load and optimizing the performance and management of the photovoltaic energy storage network.

[0069] In step 103, the impact load reduction amount of the photovoltaic energy storage station under transient overload is determined according to the impact load characteristics of each photosensitive battery group in the power load data, and the constraint cost of the charging power of the photovoltaic energy storage station under transient overload is determined by the impact load reduction amount and all energy storage adaptability.

[0070] In some embodiments, the impact load reduction amount of the photovoltaic energy storage station under transient overload is determined according to the impact load characteristics of each photosensitive battery group in the power load data, referring to Figure 2 As described above, the figure is a schematic diagram of the process of determining the impact load reduction amount in some embodiments of the present application. In this embodiment, determining the impact load reduction amount can be achieved by using the following steps:

[0071] In step 1031, for each photosensitive battery group in the photovoltaic energy storage station, a power load record of the photosensitive battery in the power load data is obtained;

[0072] In step 1032, the impact load amount of the photosensitive battery group is determined according to the power load record each time a load impact occurs in the photovoltaic energy storage station;

[0073] In step 1033, the impact load characteristics of the photosensitive battery group when the photovoltaic energy storage station has a load impact are determined through all the impact load amounts, and then the impact load characteristics of each photosensitive battery group when the photovoltaic energy storage station has a load impact are obtained;

[0074] In step 1034, the impact load reduction amount of the photovoltaic energy storage station under transient overload is determined based on all impact load characteristics.

[0075] It should be noted that in the present application, the impact load characteristics are used to describe the performance characteristics of the photosensitive battery pack in a load impact event. By extracting the impact load characteristics, the advantages and disadvantages of the photosensitive battery pack in dealing with load impacts can be identified, thereby providing quantifiable characteristic indicators, thereby improving the optimization performance of the photovoltaic energy storage station and enhancing the stability and impact resistance of the photovoltaic energy storage station; the impact load amount is an indicator used to measure the instantaneous response capability of the photosensitive battery pack to load impacts.

[0076] In specific implementation, first, for each photosensitive battery group in the photovoltaic energy storage station, the power load record of the photosensitive battery in the power load data is obtained; then, the difference between the instantaneous powers at adjacent acquisition moments in the power load record is used as the instantaneous change value of the load. When the instantaneous change value is higher than the preset impact threshold for n consecutive times (the default is 10), it indicates a load impact event in the photovoltaic energy storage station. For each load impact event when the photovoltaic energy storage station has a load impact, the maximum and minimum values ​​of the instantaneous change value in the corresponding time period of the load impact event are obtained. The difference between the maximum and minimum values ​​can be used as the impact load amount of the photosensitive battery group in the load impact event. The impact load amount of the photosensitive battery group each time a load impact occurs in the photovoltaic energy storage station can be obtained in the above manner; finally, the data features of all impact load amounts can be extracted by a feature extraction algorithm as the impact load features of the photosensitive battery group when a load impact occurs in the photovoltaic energy storage station. The impact load features of each photosensitive battery group when a load impact occurs in the photovoltaic energy storage station can be obtained in the above manner.

[0077] In step 1034 of the above embodiment, the impact load reduction amount of the photovoltaic energy storage station under transient overload is determined by all impact load characteristics, which can be achieved by the following steps:

[0078] For each photosensitive battery group in the photovoltaic energy storage station, determine all overload impact states of the photosensitive battery group;

[0079] Determine the load difference value of the photosensitive battery group under each overload impact state according to the impact load characteristics of the photosensitive battery group;

[0080] Determine the load reduction value of the photosensitive battery group under transient overload according to all load difference values, and then obtain the load reduction value of each photosensitive battery group under transient overload in the photovoltaic energy storage station;

[0081] The impact load reduction of the photovoltaic energy storage station under transient overload is determined by all impact load reductions.

[0082] It should be noted that in the present application, the impact load reduction amount is the load reduction scheduling amount required by the photovoltaic energy storage station under transient overload conditions; the load reduction value is the load power amount that the photosensitive battery group needs to reduce under transient overload conditions in order to avoid damage or performance degradation; the load difference value refers to the difference in the load power of the photosensitive battery group under overload state and normal state.

[0083] In the specific implementation, first, for each photosensitive battery group in the photovoltaic energy storage station, the power load record of the photosensitive battery group is extracted from the power load data of the photovoltaic energy storage station, and all power load information with a load state of overload is obtained in the power load record, and all states within the collection time of the load impact are screened as overload states in all power load information; then, all power load information with instantaneous change values ​​lower than the preset impact threshold for n consecutive times (the default is 10) is obtained, and the average of the average power in all power load information can be used as the normal load value of the photosensitive battery group in a normal state, and the impact load amount in each overload state is obtained in the impact load characteristics of the photosensitive battery group. For each overload state, The difference between the impact load under the overload state and the normal load value is taken as the load difference value of the photosensitive battery group under the overload impact state. The load difference value of the photosensitive battery group under each overload impact state can be obtained by the above method; then, the sum of the mean of all load difference values ​​and the minimum value of the impact load is taken as the actual impact load value, and the difference between the actual impact load value and the normal load value can be taken as the load reduction value of the photosensitive battery group under transient overload. The load reduction value of each photosensitive battery group in the photovoltaic energy storage station under transient overload can be obtained by the above method; finally, the set of all impact load reduction amounts can be taken as the value range of the impact load reduction amount of the photovoltaic energy storage station under transient overload, and the impact load reduction amount of the photovoltaic energy storage station under transient overload can be obtained.

[0084] In some embodiments, determining the constraint cost of the charging power of the photovoltaic energy storage station under transient overload by using the impact load reduction amount and all energy storage adaptability can be achieved by the following steps:

[0085] Obtain the load threshold of the photovoltaic energy storage station;

[0086] Determining a transient overload amount of the photovoltaic energy storage station by using the impact load reduction amount and the load threshold;

[0087] Determine the energy storage dispatching amount of the photovoltaic energy storage station based on all energy storage adaptability;

[0088] The constraint cost of the charging power of the photovoltaic energy storage station under transient overload is determined by the energy storage scheduling amount and the transient overload amount.

[0089] It should be noted that in this application, the constraint cost refers to the energy storage consumption cost paid to ensure the stable operation of the photovoltaic energy storage station when a transient overload occurs in the photovoltaic energy storage station; the load threshold refers to the maximum power load value that the photovoltaic energy storage station can withstand during normal operation; the transient overload amount represents the overload pressure of the photovoltaic energy storage station under transient overload conditions; the energy storage dispatch amount refers to the effective energy storage capacity that the photovoltaic energy storage station can call upon when dealing with overload.

[0090] In specific implementation, first, the load threshold can be obtained from the design and operation parameters of the photovoltaic energy storage station; secondly, for each photosensitive battery group in the photovoltaic energy storage station, the sum of the value of the photosensitive battery group in the impact load reduction (i.e., load reduction value) and the rated load value of the photosensitive battery group is taken as the transient load value, and the difference between the transient load value and the load threshold can be taken as the transient overload value of the photosensitive battery group. The transient overload value of each photosensitive battery group in the photovoltaic energy storage station can be obtained in the above manner, and the sum of all transient overload values ​​can be taken as the transient overload of the photovoltaic energy storage station; then, an energy storage scheduling model is initialized, the rated parameters of each photosensitive battery group are taken as the scheduling parameters of the intelligent scheduling model, the energy storage adaptability of each photosensitive battery group is taken as the energy storage fluctuation parameter of the intelligent scheduling model, and the photovoltaic energy storage station is evaluated for scheduling using the energy storage scheduling model, and the result of the scheduling evaluation can be taken as the energy storage scheduling amount of the photovoltaic energy storage station; finally, the ratio of the transient overload amount to the energy storage scheduling amount can be taken as the constraint cost of the charging power of the photovoltaic energy storage station under transient overload.

[0091] In step 104, the load fluctuation of each photosensitive battery group in the photovoltaic energy storage station is calibrated through the load power fluctuation smoothing strategy in the photovoltaic energy storage station and each energy storage adaptability, so as to obtain the load steady-state characteristics of each photosensitive battery group.

[0092] In some embodiments, reference Figure 3 As shown, the load power fluctuation smoothing strategy in the photovoltaic energy storage station and the adaptability of each energy storage are used to calibrate the load fluctuation of each photosensitive battery group in the photovoltaic energy storage station, and then the load steady-state characteristics of each photosensitive battery group are obtained. The following steps can be used to achieve this:

[0093] In step 1041, a load power fluctuation smoothing strategy in a photovoltaic energy storage station is obtained;

[0094] In step 1042, a fluctuation smoothing coefficient of charging power in the photovoltaic energy storage station is determined according to the fluctuation smoothing strategy and the fluctuation characteristics of charging power in the photovoltaic energy storage station;

[0095] In step 1043, the load fluctuation of each photosensitive battery group in the photovoltaic energy storage station is calibrated by using the fluctuation smoothing coefficient and each energy storage adaptability, so as to obtain the load steady-state characteristics of each photosensitive battery group.

[0096] It should be noted that in the present application, the fluctuation smoothing strategy is a management method for controlling and reducing power fluctuations in photovoltaic energy storage systems. The main purpose of the fluctuation smoothing strategy is to stabilize the power output by adjusting the operation of the energy storage system, thereby coping with power fluctuations caused by factors such as load changes and weather changes; in specific implementation, the fluctuation smoothing strategy for load power in the photovoltaic energy storage station can be obtained in the distributed photovoltaic energy storage system in the present application.

[0097] In step 1042 of the above embodiment, the following steps may be used to determine the fluctuation smoothing coefficient of the charging power in the photovoltaic energy storage station according to the fluctuation smoothing strategy and the fluctuation characteristics of the charging power in the photovoltaic energy storage station:

[0098] Determining the amount of suppression of the impact load in the photovoltaic energy storage station by the fluctuation smoothing strategy;

[0099] Determine the power abandonment loss when a load shock occurs in the photovoltaic energy storage station based on the fluctuation characteristics of the charging power in the photovoltaic energy storage station;

[0100] A fluctuation suppression coefficient of charging power in a photovoltaic energy storage station is determined according to the suppression amount and the abandoned power loss.

[0101] It should be noted that in the present application, the fluctuation smoothing coefficient reflects the regulation performance of the photovoltaic energy storage station under unstable conditions; the power abandonment loss refers to the value of electricity that cannot be stored or utilized due to the capacity limitation or insufficient regulation ability of the energy storage equipment when a load impact occurs in the photovoltaic energy storage station; the suppression amount represents the effect of the fluctuation smoothing strategy on suppressing the power fluctuation caused by the impact load in the photovoltaic energy storage station.

[0102] In the specific implementation, first, the existing simulation software can be used to conduct a large number of experiments on the quantitative values ​​of the suppression effect of the fluctuation smoothing strategy on the impact load in the photovoltaic energy storage station, and the average of the quantitative values ​​of the suppression effect in the experimental results can be used as the suppression amount of the fluctuation smoothing strategy on the impact load in the photovoltaic energy storage station; then, the difference in the charging power in the energy storage record before and after each load impact in the photovoltaic energy storage station is calculated as the energy storage fluctuation value of the charging power, the set of all energy storage fluctuation values ​​can be used as the fluctuation characteristic of the charging power in the photovoltaic energy storage station, and the calculus sum of the differences between each energy storage fluctuation value and the standard fluctuation value in the fluctuation characteristic can be used as the power abandonment loss when the photovoltaic energy storage station has a load impact; finally, the ratio of the power abandonment loss to the suppression amount can be used as the fluctuation smoothing coefficient of the charging power in the photovoltaic energy storage station.

[0103] It should be noted that in the present application, the standard fluctuation value refers to a benchmark value used to measure the degree of power fluctuation of a photovoltaic energy storage station. The standard fluctuation value is usually affected by factors such as the external environment and resistance. In specific implementation, the power fluctuation data of the photovoltaic energy storage station during normal operation can be collected, and the standard deviation of the power value in the power fluctuation data can be used as the standard fluctuation value.

[0104] In step 1043 of the above embodiment, the load fluctuation of each photosensitive battery group in the photovoltaic energy storage station is calibrated by the fluctuation smoothing coefficient and each energy storage adaptability, and the load steady-state characteristics of each photosensitive battery group are obtained, which can be achieved by the following steps:

[0105] For each photosensitive battery group, determining the energy storage volatility of the charging power in the photosensitive battery group through the energy storage adaptability of the photosensitive battery group and the fluctuation smoothing coefficient;

[0106] Calibrate the energy storage volatility of the photosensitive battery group based on the energy storage volatility to obtain the energy storage stability of the photosensitive battery group;

[0107] The load steady-state characteristics of the photosensitive battery group are determined according to the energy storage stability, and then the load steady-state characteristics of each photosensitive battery group are obtained.

[0108] It should be noted that in the present application, the load steady-state characteristic refers to the stability characteristic of the photosensitive battery group under different load conditions; the energy storage stability reflects the power stability of the photosensitive battery group under different energy storage conditions. The greater the energy storage stability, the more stable the energy storage of the photosensitive battery group; the energy storage volatility is a parameter used to measure the uncertainty of the power fluctuation of the photosensitive battery group during the energy storage process. The greater the energy storage volatility, the higher the volatility.

[0109] In the specific implementation, first, for each photosensitive battery group, the ratio of the energy storage adaptability and the fluctuation smoothing coefficient of the photosensitive battery group can be used as the energy storage volatility of the charging power in the photosensitive battery group; then, if the energy storage volatility is greater than the preset energy storage fluctuation threshold, the inverse of the energy storage volatility is used as the energy storage stability of the photosensitive battery group; if the energy storage volatility is less than or equal to the preset energy storage fluctuation threshold, the inverse of the difference between the preset energy storage fluctuation threshold and the energy storage volatility is used as the energy storage stability of the photosensitive battery group. The energy storage stability provides an intuitive indicator for the operating state of the photosensitive battery group, which is convenient for the subsequent optimization of the operating performance of each photosensitive battery group; finally, a load evaluation model is initialized, the power load record of the photosensitive battery group is used as the training base of the load evaluation model, the energy storage stability is used as the load output parameter of the load evaluation model, and the load evaluation model is used to evaluate the stability of the load of the photosensitive battery group. The result of the stability evaluation can be used as the load steady-state characteristic of the photosensitive battery group. The load steady-state characteristics of each photosensitive battery group can be obtained in the above manner.

[0110] In step 105, the power smoothing amount of each photosensitive battery group when a load impact occurs in the photovoltaic energy storage station is determined according to the steady-state characteristics of each load and the constraint cost, and the load power supply power of the photovoltaic energy storage station is balanced and smoothed based on each power smoothing amount.

[0111] In some embodiments, the power smoothing amount of each photosensitive battery group when a load shock occurs in the photovoltaic energy storage station can be determined according to the steady-state characteristics of each load and the constraint cost by using the following steps:

[0112] For each photosensitive battery group, obtain the load steady-state characteristics of the photoresistor;

[0113] Determine the load impact amplitude when a load impact occurs in the photovoltaic energy storage station;

[0114] The power smoothing amount of the photosensitive battery group when the photovoltaic energy storage station has a load impact is determined according to the load steady-state characteristics and the load impact amplitude, and then the power smoothing amount of each photosensitive battery group when the photovoltaic energy storage station has a load impact is obtained.

[0115] It should be noted that, in the present application, the power smoothing amount refers to the discharge power of the photosensitive battery group to balance the load when facing a load impact; in specific implementation, first, for each photosensitive battery group in the photovoltaic energy storage station, the load steady-state characteristics of the photoresistor are obtained; then, the maximum value of all impact load amounts of the photosensitive battery group can be used as the load impact amplitude; finally, the product of the load impact amplitude and the load steady-state characteristics can be used as the power smoothing amount of the photosensitive battery group when a load impact occurs in the photovoltaic energy storage station. The power smoothing amount of each photosensitive battery group when a load impact occurs in the photovoltaic energy storage station can be obtained in the above manner.

[0116] In some embodiments, balancing and smoothing the load power supply power of the photovoltaic energy storage station based on each power smoothing amount means: when a load impact occurs, each power smoothing amount is used as the discharge power of the corresponding photosensitive battery group in the photovoltaic energy storage station, so as to achieve balancing and smoothing of the load power supply power in the photovoltaic energy storage station.

[0117] In the present application, the power smoothing amount of each photosensitive battery group when a load impact occurs in the photovoltaic energy storage station is determined according to the steady-state characteristics of each load and the constraint cost, and the load power supply power of the photovoltaic energy storage station is balanced and smoothed based on each power smoothing amount; firstly, determining the energy storage adaptability can evaluate the energy storage capacity of different battery groups under long-term stable load conditions, thereby optimizing the configuration of energy storage resources, facilitating the subsequent balanced smoothing of load power supply power, ensuring that the photovoltaic energy storage system can effectively respond to power fluctuations under load steady state, and improving the stability of distributed photovoltaic networks under load impact; secondly, determining the impact load reduction under transient overload can accurately evaluate the performance of each battery group under load impact and the load changes it needs to withstand, and can identify potential deficiencies in the energy storage system, facilitating the formulation of effective responses to load impacts. Measures, by calculating the constraint cost, the energy storage scheduling strategy can be optimized to ensure that the energy storage system can operate stably under transient overload conditions, and by reasonably allocating energy storage resources, the impact of power fluctuations can be reduced and the load steady-state characteristics of the system can be enhanced; finally, by determining the power smoothing amount according to the load steady-state characteristics and the constraint cost, the charging power can be reasonably allocated when a load shock occurs, and balanced power smoothing can be performed when a load shock occurs in the energy storage system, reducing the impact of power fluctuations on the energy storage system. Balanced smoothing can enable the energy storage system to absorb and release power more effectively, and improve the stability of the distributed photovoltaic network when a load shock occurs; in summary, based on the above scheme, the balanced smoothing of the load power supply in the photovoltaic energy storage station can be achieved, thereby improving the load stability of the distributed photovoltaic network when a load shock occurs.

[0118] In addition, in another aspect of the present application, in some embodiments, the present application provides a distributed photovoltaic energy storage system, the distributed photovoltaic energy storage system also includes a charging power control unit, referring to Figure 4 , which is a schematic diagram of exemplary hardware and / or software of a charging power control unit according to some embodiments of the present application, and the charging power control unit includes: an acquisition module 201, a processing module 202 and an execution module 203, which are described as follows:

[0119] Acquisition module 201, in this application, acquisition module 201 is mainly used to acquire energy storage records and power load records of each photosensitive battery group in the photovoltaic energy storage station from the distributed photovoltaic network, and then obtain energy storage data and power load data;

[0120] Processing module 202, in the present application, the processing module 202 is used to determine the energy storage adaptability of each photosensitive battery group of the photovoltaic energy storage station under the load steady state according to the steady-state characteristics of the load power in the photovoltaic energy storage station and the power gradient of the energy storage data;

[0121] It should be noted that the processing module 202 is also used to determine the impact load reduction amount of the photovoltaic energy storage station under transient overload according to the impact load characteristics of each photosensitive battery group in the power load data, and determine the constraint cost of the charging power of the photovoltaic energy storage station under transient overload through the impact load reduction amount and all energy storage adaptability;

[0122] In addition, the processing module 202 is also used to calibrate the load fluctuation of each photosensitive battery group in the photovoltaic energy storage station through the load power fluctuation smoothing strategy in the photovoltaic energy storage station and each energy storage adaptability, so as to obtain the load steady-state characteristics of each photosensitive battery group;

[0123] Execution module 203, in the present application, execution module 203 is mainly used to determine the power smoothing amount of each photosensitive battery group when a load impact occurs in the photovoltaic energy storage station according to the steady-state characteristics of each load and the constraint cost, and to balance and smooth the load power supply power of the photovoltaic energy storage station based on each power smoothing amount.

[0124] The above describes in detail the examples of the distributed photovoltaic energy storage system and its power control method provided by the embodiments of the present application. It can be understood that in order to realize the above functions, the corresponding device includes hardware structures and / or software modules corresponding to the execution of each function. It should be easily appreciated by those skilled in the art that, in combination with the units and algorithm steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0125] In some embodiments, the present application also provides a computer device, which includes a memory and a processor, the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the above-mentioned distributed photovoltaic energy storage power control method.

[0126] In some embodiments, reference Figure 5 , the dotted line in the figure indicates that the unit or the module is optional, and the figure is a structural schematic diagram of a computer device for implementing a distributed photovoltaic energy storage power control method according to an embodiment of the present application. The distributed photovoltaic energy storage power control method described in the above embodiment can be Figure 5 The computer device shown in the figure is implemented, and the computer device includes at least one processor 301, a memory 302 and at least one communication unit 305. The computer device can be a terminal device, a server or a chip.

[0127] The processor 301 may be a general-purpose processor or a special-purpose processor. For example, the processor 301 may be a central processing unit (CPU), which may be used to control the computer device, execute software programs, and process data of the software programs. The computer device may also include a communication unit 305 to implement signal input (reception) and output (transmission).

[0128] For example, the computer device may be a chip, the communication unit 305 may be an input and / or output circuit of the chip, or the communication unit 305 may be a communication interface of the chip, and the chip may be a component of a terminal device, a network device, or other devices.

[0129] For another example, the computer device may be a terminal device or a server, and the communication unit 305 may be a transceiver of the terminal device or the server, or the communication unit 305 may be a transceiver circuit of the terminal device or the server.

[0130] The computer device may include one or more memories 302, on which a program 304 is stored. The program 304 can be executed by the processor 301 to generate instructions 303, so that the processor 301 performs the method described in the above method embodiment according to the instructions 303. Optionally, data (such as a target audit model) can also be stored in the memory 302. Optionally, the processor 301 can also read the data stored in the memory 302, and the data can be stored at the same storage address as the program 304, or the data can be stored at a different storage address from the program 304.

[0131] The processor 301 and the memory 302 may be provided separately or integrated together, for example, integrated on a system on chip (SOC) of the terminal device.

[0132] It should be understood that each step of the above method embodiment can be completed by a hardware-based logic circuit or software-based instructions in the processor 301. The processor 301 can be a CPU, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, such as discrete gates, transistor logic devices, or discrete hardware components.

[0133] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0134] For example, in some embodiments, the present application also provides a computer-readable storage medium, in which instructions or codes are stored. When the instructions or codes are executed on a computer, the computer implements the above-mentioned distributed photovoltaic energy storage power control method when executed.

[0135] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0136] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A distributed photovoltaic energy storage power control method, characterized in that: The steps include: Obtain the energy storage records and power load records of each photosensitive battery group in the photovoltaic energy storage station from the distributed photovoltaic network, and then obtain the energy storage data and power load data; Determine the energy storage adaptability of each photosensitive battery group of the photovoltaic energy storage station under load steady state according to the steady-state characteristics of the load power in the photovoltaic energy storage station and the power gradient of the energy storage data, wherein the energy storage adaptability reflects the adaptability of the photosensitive battery group to the load demand; Determine the impact load reduction amount of the photovoltaic energy storage station under transient overload according to the impact load characteristics of each photosensitive battery group in the power load data, and determine the constraint cost of the charging power of the photovoltaic energy storage station under transient overload through the impact load reduction amount and all energy storage adaptability; Through the load power fluctuation smoothing strategy in the photovoltaic energy storage station and the adaptability of each energy storage, the load fluctuation of each photosensitive battery group in the photovoltaic energy storage station is calibrated, and then the load steady-state characteristics of each photosensitive battery group are obtained; Determine the power smoothing amount of each photosensitive battery group when a load impact occurs in the photovoltaic energy storage station according to the steady-state characteristics of each load and the constraint cost, and balance and smooth the load power supply power of the photovoltaic energy storage station based on each power smoothing amount; Among them, determining the energy storage adaptability of each photosensitive battery group of the photovoltaic energy storage station under load steady state according to the steady-state characteristics of the load power in the photovoltaic energy storage station and the power gradient of the energy storage data specifically includes: Extracting a steady-state interval of load power from the power load data according to the steady-state characteristics of load power in the photovoltaic energy storage station; For each photosensitive battery group of the photovoltaic energy storage station under load steady state, a charging power curve of the photosensitive battery group is determined according to the power gradient of the energy storage record of the photosensitive battery group in the energy storage data; Intercepting the steady-state energy storage curve of the photosensitive battery pack in the steady-state load state from the charging power curve through the steady-state interval; The energy storage adaptability of the photosensitive battery group of the photovoltaic energy storage station under the load steady state is determined according to the steady-state energy storage curve, and then the energy storage adaptability of each photosensitive battery group of the photovoltaic energy storage station under the load steady state is obtained.

2. The method according to claim 1, characterized in that Determining the impact load reduction amount of the photovoltaic energy storage station under transient overload according to the impact load characteristics of each photosensitive battery group in the power load data specifically includes: For each photosensitive battery group in the photovoltaic energy storage station, obtaining a power load record of the photosensitive battery in the power load data; Determine the impact load of the photosensitive battery group each time a load impact occurs in the photovoltaic energy storage station according to the power load record; Determine the impact load characteristics of the photosensitive battery group when the photovoltaic energy storage station has a load impact through all the impact load amounts, and then obtain the impact load characteristics of each photosensitive battery group when the photovoltaic energy storage station has a load impact; The impact load reduction of the photovoltaic energy storage station under transient overload is determined by all impact load characteristics.

3. The method according to claim 2, characterized in that The impact load reduction of the photovoltaic energy storage station under transient overload is determined by all impact load characteristics, including: For each photosensitive battery group in the photovoltaic energy storage station, determine all overload impact states of the photosensitive battery group; Determine the load difference value of the photosensitive battery group under each overload impact state according to the impact load characteristics of the photosensitive battery group; Determine the load reduction value of the photosensitive battery group under transient overload according to all load difference values, and then obtain the load reduction value of each photosensitive battery group under transient overload in the photovoltaic energy storage station; The impact load reduction of the photovoltaic energy storage station under transient overload is determined by all impact load reductions.

4. The method according to claim 1, characterized in that The constraint cost of the charging power of the photovoltaic energy storage station under transient overload is determined by the impact load reduction and all energy storage adaptability, which specifically includes: Obtain the load threshold of the photovoltaic energy storage station; Determining a transient overload amount of the photovoltaic energy storage station by using the impact load reduction amount and the load threshold; Determine the energy storage dispatching amount of the photovoltaic energy storage station based on all energy storage adaptability; The constraint cost of the charging power of the photovoltaic energy storage station under transient overload is determined by the energy storage scheduling amount and the transient overload amount.

5. The method according to claim 1, characterized in that Through the load power fluctuation smoothing strategy in the photovoltaic energy storage station and the adaptability of each energy storage, the load fluctuation of each photosensitive battery group in the photovoltaic energy storage station is calibrated, and then the load steady-state characteristics of each photosensitive battery group are obtained, which specifically include: Obtain the load power fluctuation smoothing strategy in the photovoltaic energy storage station; Determining a fluctuation smoothing coefficient of charging power in the photovoltaic energy storage station according to the fluctuation smoothing strategy and the fluctuation characteristics of charging power in the photovoltaic energy storage station; The fluctuation of the load of each photosensitive battery group in the photovoltaic energy storage station is calibrated by the fluctuation smoothing coefficient and each energy storage adaptability, so as to obtain the load steady-state characteristics of each photosensitive battery group.

6. The method according to claim 1, characterized in that The load power supply power of the photovoltaic energy storage station is balanced and smoothed based on each power smoothing amount. When a load impact occurs, each power smoothing amount is used as the discharge power of the corresponding photosensitive battery group in the photovoltaic energy storage station to complete the load power supply power balance in the photovoltaic energy storage station.

7. A distributed photovoltaic energy storage system, which uses the method described in any one of claims 1 to 6 to control the distributed photovoltaic energy storage power, and the distributed photovoltaic energy storage system includes a charging power control unit, characterized in that: The charging power control unit comprises: An acquisition module is used to acquire energy storage records and power load records of each photosensitive battery group in a photovoltaic energy storage station from a distributed photovoltaic network, thereby obtaining energy storage data and power load data; A processing module, used to determine the energy storage adaptability of each photosensitive battery group of the photovoltaic energy storage station under load steady state according to the steady-state characteristics of the load power in the photovoltaic energy storage station and the power gradient of the energy storage data; The processing module is also used to determine the impact load reduction amount of the photovoltaic energy storage station under transient overload according to the impact load characteristics of each photosensitive battery group in the power load data, and determine the constraint cost of the charging power of the photovoltaic energy storage station under transient overload through the impact load reduction amount and all energy storage adaptability; The processing module is also used to calibrate the load fluctuation of each photosensitive battery group in the photovoltaic energy storage station through the load power fluctuation smoothing strategy in the photovoltaic energy storage station and each energy storage adaptability, so as to obtain the load steady-state characteristics of each photosensitive battery group; The execution module is used to determine the power smoothing amount of each photosensitive battery group when a load impact occurs in the photovoltaic energy storage station according to the steady-state characteristics of each load and the constraint cost, and balance and smooth the load power supply power of the photovoltaic energy storage station based on each power smoothing amount.

8. A computer device, characterized in that: The computer device includes a memory and a processor, the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the computer device executes the distributed photovoltaic energy storage power control method described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions or codes, and when the instructions or codes are executed on a computer, the computer implements the distributed photovoltaic energy storage power control method as described in any one of claims 1 to 6.

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