A distributed energy management method for photovoltaic and energy storage based on string energy storage systems

Abstract

The present invention relates to the technical field of battery energy storage management, and particularly relates to a distributed optical storage energy management method based on a string-type energy storage system, including the following steps: Step 1: Construct a regional terrain model, and calculate the theoretical conversion power based on the total power generation area of the photovoltaic panel array, the component conversion power, and the power generation loss coefficient; Step 2: Conduct a simulation calculation of sunlight irradiation to obtain the occlusion parameter value; Step 3: Analyze and calculate the coverage influence value based on the total suspended particulate matter index at the installation location; Step 4: Obtain the annual average irradiance G at the area corresponding to the installation location, and analyze and calculate the power measurement value in combination with the occlusion parameter value, the coverage influence value, and the theoretical conversion power; Step 5: Calculate the daily average power generation prediction value and the peak power generation prediction value based on the average sunshine duration and the peak sunshine duration; calculate the demand peak power of the load circuit; divide the energy storage unit into a storage unit and a circulation unit, and calculate the set quantities of the storage unit and the circulation unit.

Description

Technical Field

[0001] The present invention relates to the technical field of battery energy storage management, and particularly relates to a distributed photovoltaic and energy storage power management method based on a string-type energy storage system. Background Art

[0002] A string-type energy storage system is an energy storage solution based on modular design and intelligent control technology. By combining multiple independent energy storage units (such as battery clusters, power electronic devices, etc.) into a system, it realizes efficient storage and release of electric energy. Its core feature lies in the distributed architecture of "one cluster, one management", which can improve the flexibility, safety and reliability of the system, and is widely used in fields such as power peak shaving, new energy grid connection, industrial and commercial energy storage, and household energy storage.

[0003] In the prior art, it is difficult to comprehensively calculate the photovoltaic power generation based on the installation environment during the preparation stage of photovoltaic power generation and energy storage equipment installation, and it is impossible to adjust the type and quantity of string-type energy storage equipment based on the usage situation, resulting in poor system installation management efficiency and difficulty in achieving targeted distributed photovoltaic and energy storage installation. Summary of the Invention

[0004] In view of the above-mentioned drawbacks of the prior art, the present invention provides a distributed photovoltaic and energy storage power management method based on a string-type energy storage system, which can effectively solve the problem in the prior art that it is impossible to adjust and match the type and quantity of string-type energy storage equipment in combination with the photovoltaic and energy storage power generation and load usage situations.

[0005] To achieve the above object, the present invention is realized through the following technical solutions:

[0006] The present invention provides a distributed photovoltaic and energy storage power management method based on a string-type energy storage system, including the following steps:

[0007] Step 1: Construct a regional terrain model of the installation location and its surrounding area, and set a photovoltaic panel array model therein. Calculate the theoretical conversion power based on the total power generation area, component conversion power, and power generation loss coefficient of the photovoltaic panel array;

[0008] Step 2: Construct a plurality of solar movement axes in the regional terrain model. The plurality of solar movement axes are arrayed within a preset angular range, and a plurality of irradiation analysis points are provided on the solar movement axes;

[0009] Perform sunlight irradiation simulation at different irradiation analysis points to obtain the shadow coverage ratio on the photovoltaic panel array. Calculate the shadow influence value based on the shadow coverage ratio. Calculate the first influence value and the second influence value respectively based on the peak value of the shadow influence value and the proportion of the number of shadow influence values greater than 0 at each irradiation analysis point, and combine the two to calculate the occlusion parameter value;

[0010] Step 3: Obtain the total suspended particulate index monitored at multiple sampling times at the installation location and analyze and calculate the coverage influence value;

[0011] Step 4: Obtain the annual average irradiance of the corresponding area at the installation location and denote it as G. Combine the occlusion parameter value, the coverage influence value, and the theoretical conversion power to analyze and calculate the power measurement value;

[0012] Step 5: Calculate the daily average power generation prediction value and the peak power generation prediction value based on the average sunshine duration and the peak sunshine duration;

[0013] Calculate the peak demand power of the load circuit;

[0014] Divide the energy storage unit into a storage unit and a circulation unit, obtain the energy storage power of each energy storage unit, and combine the daily average power generation prediction value, the peak power generation prediction value, the daily average usage duration, the late average usage duration, and the peak demand power to calculate the quantity setting values of the storage unit and the circulation unit respectively.

[0015] Further, the process of constructing the regional terrain model is as follows:

[0016] Denote the installation location and its surrounding area as the target area, use a drone to perform a horizontal height scan on the target area, construct a height distribution map within the target area. The height distribution map includes multiple unit areas, and each unit area corresponds to a height value;

[0017] Obtain the height value of the installation location and denote it as the height threshold. Exclude the unit areas within the target area where the height value is less than or equal to the height threshold to obtain multiple influence areas. Each influence area contains one or more adjacent unit areas;

[0018] Construct a column model of the influence area in the height distribution map. The column model includes multiple unit columns, and each unit column corresponds to a unit area. The height of the unit column is equal to the height value of the unit area. Denote the height distribution map containing the column model as the regional terrain model, and construct a photovoltaic panel array model in the regional terrain model.

[0019] Further, the process of constructing the height distribution map is as follows:

[0020] Obtain the plane map within the target area, divide the plane map into multiple unit areas, where the side length of each unit area is less than or equal to a preset precision threshold. Mark the center point of the unit area as the scan point, construct a flight trajectory connecting each scan point, control the drone to fly along the flight trajectory, and use the onboard lidar to scan the ground at each scan point to obtain the height measurement value of the scan point as the height value of the unit area.

[0021] Further, the process of calculating the shadow influence value is as follows:

[0022] Each irradiation analysis point is denoted as , where i represents the serial number corresponding to the solar movement axis, and j represents the serial number of the irradiation analysis point on the corresponding solar movement axis. When simulating sunlight irradiation at each irradiation analysis point, the shadow area formed on the photovoltaic panel array is obtained , and substituted into the formula for calculation to obtain the shadow coverage ratio , where represents the total power generation area of the photovoltaic panel array;

[0023] The shadow coverage ratio is substituted into the formula for calculation to obtain the shadow influence value DF corresponding to each irradiation analysis point, where are all preset weight coefficients, and e is the natural constant;

[0024] Let the shadow influence value corresponding to the irradiation analysis point be , and the peak value of the shadow influence value on each solar movement axis is obtained and denoted as , and substituted into the formula for calculation to obtain the first influence value , where n is the total number of solar movement axes.

[0025] Furthermore, the calculation process of the occlusion parameter value is as follows:

[0026] Let the shadow influence value corresponding to the irradiation analysis point be , and the peak value of the shadow influence value on each solar movement axis is obtained and denoted as , and substituted into the formula for calculation to obtain the first influence value , where n is the total number of solar movement axes;

[0027] The number of shadow influence values greater than 0 is obtained and denoted as , and substituted into the formula for calculation to obtain the second influence value , where m is the total number of irradiation analysis points on the same solar movement axis;

[0028] The first influence value and the second influence value are normalized and then substituted into the formula for calculation to obtain the occlusion parameter value , where are all preset weight coefficients.

[0029] Furthermore, the calculation process of the coverage influence value is as follows:

[0030] Preset a monitoring period, obtain the total suspended particulate matter index monitored at the installation location within the most recent monitoring period. Set multiple sampling times within the monitoring period, and the multiple sampling times are evenly distributed within the monitoring period. Extract the total suspended particulate matter index corresponding to the sampling time and denote it as the sampling index;

[0031] Construct a rectangular coordinate system and draw a line graph of the sampling index changing with the sampling time. Preset a cleaning period, which refers to the cleaning period of the photovoltaic panel array. Divide the line graph of the sampling index changing with the sampling time into multiple interval segments with the cleaning period as the interval length , where f is the serial number of the interval segment;

[0032] Calculate the area of the closed image enclosed between each interval segment and the time axis to obtain the cumulative index , substitute it into the formula for calculation to obtain the coverage influence value ;

[0033] where h is the total number of interval segments, T is the duration of the cleaning period, is a preset empirical coefficient.

[0034] Furthermore, the calculation process of the power measurement value is as follows:

[0035] Obtain the annual average irradiance corresponding to the installation location and denote it as G, extract the occlusion parameter value and the coverage influence value and perform normalization processing. Combine with the theoretical conversion power , substitute it into the formula for calculation to obtain the power measurement value P, where are all preset proportional coefficients.

[0036] Furthermore, the process of setting the number of storage units and loop units is as follows:

[0037] Obtain the average sunshine duration of the area where the installation location is located and denote it as , multiply the average sunshine duration by the power measurement value P to obtain the predicted daily power generation value , obtain the peak sunshine duration of the area where the installation location is located and denote it as , multiply the average sunshine duration by the power measurement value P to obtain the predicted peak power generation value ;

[0038] Obtain the rated powers of multiple electrical devices in the load circuit , the daily average usage duration and the evening average usage duration , where q is the serial number of the electrical equipment, substitute it into the formula:

[0039] Perform the calculation to obtain the peak demand electricity ;

[0040] where is the longest continuous rainy days in the area where the installation location is located;

[0041] Obtain the energy storage electricity of each storage unit and each cycling unit and record them as , substitute it into the formula:

[0042] Perform the calculation to obtain the set values of the number of storage units and cycling units respectively ;

[0043] where is the optimal cycling electricity ratio of the cycling unit, is the optimal energy storage electricity ratio of the energy storage unit, is the preset proportionality coefficient.

[0044] A computer device includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, it implements the steps of the above method.

[0045] A computer-readable storage medium stores a computer program. When the computer program is executed by a processor, it implements the steps of the above method.

[0046] The technical solution provided by the present invention has the following beneficial effects compared with the known prior art:

[0047] 1. By comprehensively considering the occlusion parameter value and the coverage influence value, the present invention can further consider the environmental data around the installation location when measuring the energy storage power of the distributed photovoltaic power generation system, incorporate the obstacle shadow occlusion and dust coverage into the influence range, so as to obtain a more accurate power generation prediction value. Compared with the power generation power calculation method in the prior art, more factors are considered, and it is more suitable for the pre-installation evaluation of the photovoltaic power generation system under the condition of variable environmental factors, so as to reasonably set the number of energy storage units in the string-type energy storage system and reduce the redundant setting of energy storage units.

[0048] 2. The present invention benefits from the string-type energy storage system. By distinguishing the storage unit and the circulation unit, and then calculating the required quantity of different energy storage units respectively according to the load demand and energy storage demand during actual use, and thus making an adaptive combination according to the required quantity to obtain a personalized string-type energy storage system. Furthermore, on the premise of meeting the various usage requirements of the installation site, the usage efficiency of the string-type energy storage system is effectively improved, while the installation cost of the energy storage system is saved and unnecessary expenditures are reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained according to these drawings.

[0050] Figure 1 It is the overall module block diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0051] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0052] The following further describes the present invention with reference to the embodiments.

[0053] Refer to Figure 1 , a distributed photovoltaic energy storage management method based on a string-type energy storage system, which at least includes a distributed photovoltaic power generation system. The distributed photovoltaic power generation system refers to a power generation system including a photovoltaic power generation panel array, a photovoltaic controller, a string-type energy storage system, an inverter, and a corresponding energy storage power station joint control and dispatching system, etc. The photovoltaic module array absorbs solar energy and converts it into electrical energy, which is stored in the string-type energy storage system or input into the load circuit through the inverter.

[0054] It should be noted that the distributed photovoltaic power generation system is generally divided into two modes, namely the grid-connected mode and the off-grid mode. In the grid-connected mode, the distributed photovoltaic power generation system can feed the excess electrical energy exceeding the local load demand into the public grid through the grid-connected inverter, while in the off-grid mode, the distributed photovoltaic power generation system will store the electrical energy in the energy storage unit of the string-type energy storage system and use it for the local load circuit. The management method in the present invention mainly aims at the distributed photovoltaic power generation system in the off-grid mode.

[0055] It also includes the following steps:

[0056] Step 1: Construct a regional terrain model and analyze and calculate the theoretical conversion power of the photovoltaic panel array, where:

[0057] Record the installation location and its surrounding area (in a specific embodiment, the surrounding area refers to a square area with a side length of 100 m centered on the installation location) as the target area, use a drone to perform a horizontal height scan of the target area, and construct a height distribution map of the target area. The construction process of the height distribution map is as follows:

[0058] Obtain a planar map of the target area, divide the planar map into multiple unit areas, the side length of each unit area is less than or equal to a preset precision threshold (in a specific embodiment, the precision threshold is set to 0.5 m), mark the center point of the unit area as the scan point, construct a flight trajectory connecting each scan point, control the drone to fly along the flight trajectory, and use an on-board lidar (LiDAR) to scan the ground at each scan point to obtain the height measurement value of the scan point as the height value of the unit area;

[0059] It should be noted that the height distribution map is a two-dimensional planar map of the target area. Each unit area in the height distribution map corresponds to a height value, that is, the actual height of the unit area. Through the height distribution map, the terrain height situation in the target area can be understood, so as to screen out the areas that may affect the power generation efficiency of the photovoltaic panel array.

[0060] Obtain the height value of the installation location and record it as the height threshold. Exclude the unit areas in the target area with height values less than or equal to the height threshold to obtain multiple influence areas. Each influence area contains one or more adjacent unit areas (the unit areas that make up the influence area all satisfy that the height value is higher than the height threshold). Construct a columnar model of the influence area in the height distribution map. The columnar model includes multiple unit columns. Each unit column corresponds to a unit area, and the height of the unit column is equal to the height value of the unit area. Record the height distribution map containing the columnar model as the regional terrain model (the regional terrain model is a three-dimensional map formed by introducing a columnar model on the basis of a two-dimensional height distribution map). Mark the installation area corresponding to the photovoltaic panel array in the regional terrain model. The installation area refers to the installation area of the photovoltaic panel array in the distributed photovoltaic power generation system. Construct a photovoltaic panel array model in the installation area;

[0061] By constructing the regional terrain model, the digital display of the terrain environment data of the installation location and its surroundings is realized, so as to facilitate the three-dimensional simulation of the installation situation of the photovoltaic panel array in the subsequent process, and predictions and estimations can be made for some data without actual installation.

[0062] The total power generation area of ​​the photovoltaic panel array is obtained and recorded as A. The total power generation area is equal to the sum of the power generation areas of all photovoltaic panel arrays. The component conversion power of the photovoltaic panel array is obtained and recorded as η. The power generation loss coefficient of the photovoltaic panel array (i.e., the comprehensive line loss and inverter loss, which is 20% in a specific embodiment) is obtained and recorded as Z. The conversion power calculation formula is , calculate the theoretical conversion power ;

[0063] It should be noted that the theoretical conversion power refers to the equivalent conversion power of the photovoltaic panel array to convert solar irradiance (light intensity) into electrical energy under ideal working conditions, without considering equipment attenuation and environmental influences. When the solar irradiance is fixed, the greater the theoretical conversion power, the higher the power generation power of the photovoltaic panel array.

[0064] Step 2: An angle interval is preset, which corresponds to the variation range of the solar altitude angle at noon in the target area. Multiple solar moving axes are constructed in the regional terrain model to simulate the rotation path of the sun relative to the target area during the day. The multiple solar moving axes are evenly distributed in the angle interval (that is, the intervals between the multiple solar moving axes are fixed angle values ​​that conform to the array distribution). Multiple illumination analysis points are set on each solar moving axis, and each illumination analysis point is used as a light source to simulate sunlight illumination (a parallel light source is used to simulate light illumination to obtain shadow distribution).

[0065] It should be noted that the solar altitude angle in the target area will change at the same time every day as the earth revolves. This change cycle is usually one year (i.e., the time it takes for the earth to revolve once), which affects the size of the shadow area formed by sunlight, and thus affects the photovoltaic panel array. Light irradiation simulation is an existing technology. For example, SketchUp software in the existing technology can simulate the shadow effect under a three-dimensional model.

[0066] Each irradiation analysis point is recorded as , where i represents the serial number of the corresponding sun moving axis, and j represents the serial number of the irradiation analysis point on the corresponding sun moving axis, for example Indicates the irradiation analysis point with serial number 1 on the sun moving axis with serial number 1. When simulating sunlight irradiation at each irradiation analysis point, obtain the shadow area formed on the photovoltaic panel array , substitute into the formula Calculate the shadow coverage ratio ,in represents the total power generation area of ​​the photovoltaic panel array, and substitutes the shadow coverage ratio into the formula Calculate in and get the shadow impact value DF corresponding to each irradiation analysis point, where are all preset weight coefficients, and \(e\) is the natural constant;

[0067] Let the irradiation analysis point The corresponding shadow influence value is , and obtain the peak value of the shadow influence value on each solar movement axis, denoted as , substitute it into the formula for calculation to obtain the first influence value , where \(n\) is the total number of solar movement axes;

[0068] Obtain the number of shadow influence values greater than 0, denoted as , substitute it into the formula for calculation to obtain the second influence value , where \(m\) is the total number of irradiation analysis points on the same solar movement axis;

[0069] Obtain the first influence value and the second influence value After normalization, substitute them into the formula for calculation to obtain the occlusion parameter value , where are all preset weight coefficients.

[0070] It should be noted that the occlusion parameter value is a parameter value obtained by simulating shadow coverage using 3D model shadow processing software on the basis of the regional terrain model and calculating through a mathematical analysis formula. The occlusion parameter value reflects the influence of the shadow area formed by the surrounding buildings (or trees) at the installation location on the photovoltaic power generation efficiency under sunlight irradiation. This value is not simulated based on the lighting conditions of a certain day, but is obtained through comprehensive analysis of multi-point simulations over a long period (one year in this embodiment). It can comprehensively simulate the influence of the shadow of surrounding obstacles at the installation location on the photovoltaic power generation efficiency at different dates and times, and conduct summary analysis to facilitate the measurement of the actual energy storage power of the distributed photovoltaic power generation system under long-term use.

[0071] Step 3: Preset a monitoring period (in a specific embodiment, the monitoring period is set to 1 year), obtain the total suspended particulate matter (TSP) index monitored at the installation location in the most recent monitoring period. Set multiple sampling times within the monitoring period, and the multiple sampling times are evenly distributed within the monitoring period. Extract the total suspended particulate matter index corresponding to the sampling time and denote it as the sampling index;

[0072] Construct a rectangular coordinate system (the horizontal axis is the time axis and the vertical axis is the total suspended particulate matter index value) and draw a line graph of the sampling index changing with the sampling time. A cleaning cycle is preset, and the cleaning cycle refers to the cleaning cycle of the photovoltaic panel array (the surface of the photovoltaic panel array needs to be cleaned every other cleaning cycle to remove the covered dust). Divide the line graph of the sampling index changing with the sampling time into multiple interval segments with the cleaning cycle as the interval length. where f is the serial number of the interval segment, and the projection length of each interval segment on the time axis is equal to the cleaning cycle;

[0073] Calculate the area of the closed image enclosed by each interval segment and the time axis to obtain the cumulative index Substitute it into the formula for calculation to obtain the coverage influence value where h is the total number of interval segments, T is the duration of the cleaning cycle, is a preset empirical coefficient.

[0074] It should be noted that the cleaning cycle of the photovoltaic panel array is generally set to multiple times a year in actual applications. Therefore, the line graph of the sampling index changing with the sampling time can be exactly divided into an integer number of interval segments, and the projection lengths of each interval segment are equal. By analyzing the total suspended particulate matter index within the monitoring cycle and combining the coverage influence value calculated by image processing technology, it can indirectly reflect the influence degree of dust coverage on the efficiency of the photovoltaic panel array during use, so as to facilitate further analysis of the energy storage power in the actual use process of the distributed photovoltaic power generation system.

[0075] Step 4: Obtain the annual average irradiance G corresponding to the installation location, extract the occlusion parameter value and the coverage influence value and perform normalization processing. Combine the theoretical conversion power Substitute it into the formula for calculation to obtain the power measurement value P, where are all preset proportional coefficients.

[0076] It should be noted that by comprehensively considering the occlusion parameter value and the coverage influence value, when calculating the energy storage power (i.e., the power generation power) of the distributed photovoltaic power generation system, the environmental data around the installation location can be further considered, and the obstacle shadow occlusion and dust coverage are included in the influence range, so as to obtain a more accurate power generation power prediction value. Compared with the power generation power calculation method in the prior art, more factors are considered, and it is more suitable for the pre-installation evaluation of the photovoltaic power generation system under the condition of variable environmental factors, so as to reasonably set the number of energy storage units in the string-type energy storage system and reduce the redundant setting of energy storage units.

[0077] Step Five: Obtain the average sunshine duration in the area where the installation location is located and denote it as , multiply the average sunshine duration by the power measurement value P to obtain the daily average power generation prediction value , obtain the peak sunshine duration in the area where the installation location is located and denote it as , multiply the average sunshine duration by the power measurement value P to obtain the peak power generation prediction value ;

[0078] Obtain the rated power of multiple electrical devices in the load circuit , the daily average usage duration and the evening average usage duration , where q is the serial number of the electrical device, substitute into the formula:

[0079] for calculation to obtain the demand peak power , where is the maximum number of consecutive rainy days in the area where the installation location is located, that is, the maximum value of the number of consecutive rainy days;

[0080] It should be noted that the rated power can be obtained from the data nameplate of the electrical device, and the daily average usage duration is obtained by the registration of the staff at the installation site.

[0081] Divide the energy storage unit into a storage unit and a cycling unit. The energy storage battery in the storage unit is mainly used for electrical energy storage, and the energy storage battery in the cycling unit is mainly used for supplying power to the load. Obtain the energy storage power of each storage unit and each cycling unit and denote them as , substitute into the formula:

[0082] for calculation to respectively obtain the set values of the number of storage units and cycling units , where is the optimal cycling power ratio of the cycling unit, is the optimal energy storage power ratio of the energy storage unit, is the preset proportional coefficient.

[0083] It should be noted that different types of battery clusters (i.e., energy storage units) have different advantages in terms of functional uses. Generally (i.e., in the case of a centralized energy storage system), different types of energy storage units cannot be combined. Thanks to the string-type energy storage system, it is possible to achieve the combined use of different types of energy storage units and give play to the advantages of various batteries. For example, lead-acid batteries with good storage performance, storage stability and low cost can be selected as energy storage units, while lithium batteries with good cycle life and charge-discharge efficiency can be selected as cycle units. In addition, the optimal cycle power ratio refers to the ideal service life that the corresponding battery can reach when cycling within this power ratio. For example, the optimal cycle ratio of general lithium batteries is 60%. Similarly, the optimal energy storage power ratio refers to the ideal service life that the corresponding battery can reach when storing electricity within this power ratio. For example, the optimal energy storage power ratio of general lead-acid batteries is 80%.

[0084] By distinguishing between storage units and cycle units, and then calculating the required quantities of different energy storage units respectively according to the load demand and energy storage demand during actual use, and then making an adaptive combination according to the required quantities to obtain a personalized string-type energy storage system, thereby effectively improving the use efficiency of the string-type energy storage system while meeting the various use requirements of the installation site, saving the installation cost of the energy storage system and reducing unnecessary expenditures.

[0085] A computer device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps in the above method are implemented.

[0086] A computer-readable storage medium stores a computer program thereon, and when the computer program is executed by a processor, the steps in the above method are implemented.

[0087] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the protection scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A distributed photovoltaic energy storage management method based on a string energy storage system, characterized in that: The following steps are involved: Step 1: Construct a regional terrain model of the installation location and its surrounding area and set a photovoltaic panel array model therein, and calculate the theoretical conversion power based on the total power generation area of ​​the photovoltaic panel array, the component conversion power, and the power generation loss coefficient; Step 2: construct multiple solar moving axes in the regional terrain model, wherein the arrays of the multiple solar moving axes are distributed within a preset angle range, and multiple irradiation analysis points are set on the solar moving axes; Perform sunlight irradiation simulation at different irradiation analysis points to obtain the shadow coverage ratio on the photovoltaic panel array, calculate the shadow impact value based on the shadow coverage ratio, and calculate the first impact value and the second impact value according to the peak value of the shadow impact value of each irradiation analysis point and the proportion of the number of shadow impact values ​​greater than 0, and combine the two to calculate the shading parameter value; Step 3: Obtain the total suspended particulate matter index monitored at multiple sampling times at the installation location and analyze and calculate the coverage impact value; Step 4: Obtain the annual average irradiance of the area corresponding to the installation location, recorded as G, and calculate the power measurement value by combining the shielding parameter value, coverage influence value, and theoretical conversion power analysis; Step 5: Calculate the average daily power generation forecast value and the peak power generation forecast value based on the average sunshine duration and the peak sunshine duration; Calculate the peak power demand of the load circuit; The energy storage units are divided into storage units and circulation units, and the storage capacity of each energy storage unit is obtained. Combined with the average daily power generation forecast value, peak power generation forecast value, average daily usage time, average evening usage time, and peak power demand, the number setting values ​​of storage units and circulation units are calculated respectively.

2. A distributed photovoltaic energy storage management method based on a string energy storage system according to claim 1, characterized in that: The regional terrain model construction process is as follows: The installation location and its surrounding area are recorded as the target area, and a drone is used to perform horizontal height scanning on the target area to construct a height distribution map within the target area. The height distribution map includes multiple unit areas, and each unit area corresponds to a height value; The height value of the installation position is obtained and recorded as a height threshold, and the unit areas with height values ​​less than or equal to the height threshold in the target area are eliminated to obtain multiple influence areas, each of which includes one or more adjacent unit areas; A columnar model of the affected area is constructed in the height distribution map. The columnar model includes multiple unit columns, each unit column corresponds to a unit area, and the height of the unit column is equal to the height value of the unit area. The height distribution map containing the columnar model is recorded as a regional terrain model, and a photovoltaic panel array model is constructed in the regional terrain model.

3. A distributed photovoltaic energy storage management method based on a string energy storage system according to claim 2, characterized in that: The height distribution map construction process is as follows: Obtain a plane map within the target area, divide the plane map into multiple unit areas, the side length of each unit area is less than or equal to the preset accuracy threshold, mark the center point of the unit area as the scanning point, build a flight trajectory connecting each scanning point, control the UAV to fly along the flight trajectory, use the airborne laser radar to scan the ground at each scanning point, and obtain the height measurement value of the scanning point as the height value of the unit area.

4. A distributed photovoltaic energy storage management method based on a string energy storage system according to claim 1, characterized in that: The shadow impact value calculation process is as follows: Each irradiation analysis point is recorded as , where i represents the serial number of the corresponding sun moving axis, j represents the serial number of the irradiation analysis point on the corresponding sun moving axis, and when simulating sunlight irradiation at each irradiation analysis point, the shadow area formed on the photovoltaic panel array is obtained , substitute into the formula Calculate the shadow coverage ratio ,in Represents the total power generation area of ​​the photovoltaic panel array; Substituting the shadow coverage ratio into the formula Calculate in and get the shadow impact value DF corresponding to each irradiation analysis point, where are all preset weight coefficients, and e is a natural constant; Set irradiation analysis point The corresponding shadow impact value is , obtain the peak value of the shadow impact value on each sun moving axis and record it as , substitute into the formula The first impact value is calculated , where n is the total number of the sun's moving axes.

5. A distributed photovoltaic energy storage management method based on a string energy storage system according to claim 4, characterized in that: The occlusion parameter value calculation process is as follows: Set irradiation analysis point The corresponding shadow impact value is , obtain the peak value of the shadow impact value on each sun moving axis and record it as , substitute into the formula The first impact value is calculated , where n is the total number of the sun's moving axes; Get the number of shadow influence values ​​greater than 0 and record it as , substitute into the formula The second influence value is calculated by , where m is the total number of irradiation analysis points on the same sun moving axis; Get the first impact value and the second impact value After normalization, enter the formula Calculate the occlusion parameter value ,in These are all preset weight coefficients.

6. A distributed photovoltaic energy storage management method based on a string energy storage system according to claim 1, characterized in that: The calculation process of the coverage impact value is as follows: A monitoring cycle is preset, and the total suspended particulate matter index monitored at the installation location in the most recent monitoring cycle is obtained. Multiple sampling moments are set in the monitoring cycle, and the multiple sampling moments are evenly distributed in the monitoring cycle. The total suspended particulate matter index corresponding to the sampling moment is extracted and recorded as the sampling index; Construct a rectangular coordinate system and draw a line graph of the sampling index changing with the sampling time. A cleaning cycle is preset. The cleaning cycle refers to the cleaning cycle of the photovoltaic panel array. The line graph of the sampling index changing with the sampling time is divided into multiple interval segments with the cleaning cycle as the interval length. , where f is the serial number of the interval segment; Calculate each interval segment The closed image area enclosed by the time axis is used to obtain the cumulative index , substitute into the formula The coverage impact value is calculated in ; Where h is the total number of interval segments, T is the duration of the cleaning cycle, is the preset empirical coefficient.

7. A distributed photovoltaic energy storage management method based on a string energy storage system according to claim 1, characterized in that: The power measurement value calculation process is as follows: Get the annual average irradiance of the area corresponding to the installation location, recorded as G, and extract the shielding parameter value , Overwrite Impact Value And normalized, combined with the theoretical conversion power , substitute into the formula Calculate in and get the power measurement value P, where These are preset scaling factors.

8. A distributed photovoltaic energy storage management method based on a string energy storage system according to claim 1, characterized in that: The process of setting the number of storage units and circulation units is as follows: Get the average sunshine duration in the area where the installation is located and record it as , the average sunshine duration Multiply by the power calculation value P to get the daily average power generation forecast value , obtain the peak sunshine duration in the area where the installation is located and record it as , the average sunshine duration Multiply by the power calculation value P to get the peak power generation forecast value ; Get the rated power of multiple electrical devices in the load circuit , average daily usage time and average nightly usage time , where q is the serial number of the electrical equipment, substitute into the formula: Calculate and get the peak power demand ; in The longest number of rainy days in the installation location; The energy storage capacity of each storage unit and each cycle unit is recorded as , substitute into the formula: Calculate and get the setting values ​​of storage unit and circulation unit quantity respectively ; in is the optimal cycle power ratio of the cycle unit, is the optimal energy storage capacity ratio of the energy storage unit, is the preset scaling factor.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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