Distributed energy storage converter voltage fluctuation suppression method suitable for seasonal load

Abstract

The invention discloses a distributed energy storage converter voltage fluctuation suppression method suitable for seasonal load, and belongs to the technical field of voltage fluctuation suppression, and the method comprises the steps: marking a target region, obtaining a target region information graph, and setting each seasonal unit region according to the target region information graph; the seasonal unit area is an electricity utilization area meeting seasonal load requirements; determining each energy storage regulation and control area according to each season unit area, and setting energy storage equipment according to each energy storage regulation and control area; setting a voltage suppression scheme according to a preset energy storage reference adjustment principle and the energy storage equipment of each energy storage regulation and control region; establishing a load prediction model, performing real-time data acquisition according to each preset acquisition item to obtain load condition data, and analyzing the load condition data through the load prediction model to obtain load prediction data; and analyzing the load prediction data according to the voltage suppression scheme to obtain a control instruction of each energy storage device, and controlling each energy storage device according to each control instruction.

Description

Technical Field

[0001] The invention belongs to the technical field of voltage fluctuation suppression, and in particular is a method for suppressing voltage fluctuation of a distributed energy storage converter suitable for seasonal loads. Background Art

[0002] Seasonal load changes are common in power systems, such as in rural areas, cities, residential areas, and certain specific industries. The sharp increase in air conditioning loads in summer and heating loads in winter has put tremendous pressure on the power grid. Such load changes can cause grid voltage fluctuations, which in turn affects the normal operation of electrical equipment. Traditional grid regulation methods often have difficulty in responding quickly to such seasonal load fluctuations, resulting in unstable grid voltage and reduced power supply reliability.

[0003] With the transformation of energy structure and the development of smart grid, distributed energy storage converters have received extensive attention and application as an important means to improve the flexibility and reliability of power grids. Therefore, how to better combine distributed energy storage converters to suppress voltage fluctuations of seasonal loads has become a problem that needs to be solved.

[0004] Based on this, the present invention provides a method for suppressing voltage fluctuations of a distributed energy storage converter suitable for seasonal loads. Summary of the invention

[0005] In order to solve the problems existing in the above-mentioned solutions, the present invention provides a method for suppressing voltage fluctuations of a distributed energy storage converter suitable for seasonal loads.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A method for suppressing voltage fluctuation of a distributed energy storage converter suitable for seasonal loads comprises the following steps:

[0008] Step 1: Mark the target area, obtain the target area information map, and set each seasonal unit area according to the target area information map; the seasonal unit area is the power consumption area that meets the seasonal load requirements;

[0009] Step 2: Determine each energy storage control area according to each seasonal unit area, and set up energy storage equipment according to each energy storage control area;

[0010] Step 3: Setting a voltage suppression plan based on the preset energy storage benchmark adjustment principle and the energy storage equipment in each energy storage control area;

[0011] Step 4: Establish a load forecasting model, collect real-time data according to preset collection items, obtain load condition data, analyze the load condition data through the load forecasting model, and obtain load forecast data;

[0012] Step 5: Analyze the load forecast data according to the voltage suppression scheme, obtain the control instructions of each energy storage device, and control each energy storage device according to the control instructions.

[0013] Furthermore, the step of setting each seasonal unit area according to the target area information map includes:

[0014] Setting a unit area definition, identifying the target area information map according to the unit area definition, and marking each unit area in the target area information map according to the identification result; obtaining historical power consumption data of each unit area and marking it as unit data;

[0015] Setting seasonal load requirements, and setting a seasonality determination model according to the seasonal load requirements;

[0016] Analyze the unit data of each unit area by using the seasonal judgment model to obtain the seasonal judgment value corresponding to each unit area;

[0017] Each unit area having a seasonal judgment value of 1 is marked as a seasonal unit area.

[0018] Furthermore, the seasonality judgment model is expressed as:

[0019]

[0020] In the formula: s is the input data, the input data is the unit data; the output data is the seasonal judgment value PH(s).

[0021] Furthermore, the method for setting the energy storage control area includes:

[0022] Step SA1: Obtaining energy storage device performance data;

[0023] Step SA2: Select any seasonal unit area as the initial area; if there is no initial area,

[0024] Go to step SA7;

[0025] Acquire regional association data between the initial region and each seasonal unit region; set merging requirements;

[0026] According to the corresponding regional association data, it is evaluated whether the initial region and each seasonal unit region meet the merging requirements, and each seasonal unit region that meets the merging requirements is marked as the region to be evaluated of the initial region;

[0027] Step SA3: combining the initial area with the corresponding area to be evaluated to form an initial combination; when there is no area to be evaluated, step SA2;

[0028] Analyzing the initial combination through energy storage device performance data to obtain a performance evaluation result, wherein the performance evaluation result includes whether the performance requirements are met or not met;

[0029] Step SA4: When the performance evaluation result is that the performance requirement is not met, the corresponding initial combination is prohibited; and the process returns to step SA3;

[0030] When the performance evaluation result satisfies the performance requirements, the initial combination is marked as a combined combination; the combined combination is combined with the corresponding area to be evaluated to form a new initial combination; the initial combination is analyzed through the energy storage device performance data to obtain a new performance evaluation result;

[0031] Step SA5: When the performance evaluation result is that the performance requirement is not met, the corresponding initial combination is prohibited, the combination mode corresponding to the corresponding merged combination is output, and the process returns to step SA3;

[0032] When the performance evaluation result satisfies the performance requirements, the corresponding initial combination is marked as a new combined combination; the new combined combination is combined with the corresponding area to be evaluated to form a new initial combination; the initial combination is analyzed through the energy storage device performance data to obtain a new performance evaluation result;

[0033] Step SA6: loop step SA5;

[0034] Step SA7: identifying various combinations, and forming various control schemes to be selected according to the various combinations;

[0035] Performing a control evaluation on each of the selected control schemes to obtain a corresponding control evaluation result, wherein the control evaluation result includes a control evaluation qualified and a control evaluation unqualified;

[0036] Step SA8: Marking each of the candidate control schemes merged by the control evaluation as a to-be-applied scheme, and determining a target application scheme from each of the to-be-applied schemes;

[0037] Identify the various combination methods corresponding to the target application solutions, and integrate the seasonal unit areas corresponding to the combination methods into an energy storage control area.

[0038] Furthermore, the method of performing control evaluation on each candidate control scheme in step SA7 includes:

[0039] Set simulation data for the scheme based on historical electricity consumption data of the target area; set energy storage benchmark adjustment principles;

[0040] Simulate each candidate control scheme according to the energy storage benchmark adjustment principle and scheme simulation data to obtain corresponding simulation verification data; identify the benchmark simulation results corresponding to the scheme simulation data;

[0041] Compare the benchmark simulation results with each simulation verification data, determine the inhibition effect ranking corresponding to each simulation verification data, and rank each candidate control scheme according to the inhibition effect ranking to obtain a first sequence;

[0042] Obtaining a voltage suppression target, eliminating each candidate control scheme that is lower than the voltage suppression target from the first sequence, and obtaining a second sequence;

[0043] Counting the vacancy rates corresponding to the candidate control schemes in the second sequence, and removing the candidate control schemes with vacancy rates lower than the threshold value X1 from the second sequence, to obtain a third sequence;

[0044] The regulatory assessment results of each candidate regulatory scheme in the third sequence are deemed to be qualified in the regulatory assessment;

[0045] The regulatory assessment results of each candidate regulatory scheme not in the third sequence shall be deemed as unqualified in the regulatory assessment.

[0046] Furthermore, the energy storage benchmark adjustment principle is: when the predicted load increases, charging is performed within a preset time period; when the predicted load decreases, discharging is performed within a preset time period.

[0047] Furthermore, the load forecasting model is established based on a deep neural network, the input data is load condition data, and the output data is load forecasting data.

[0048] A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the method for suppressing voltage fluctuations of a distributed energy storage converter applicable to seasonal loads as described above is implemented.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] By optimizing the control strategy of distributed energy storage inverters, the voltage fluctuations caused by seasonal load changes can be effectively suppressed, the stability of the grid voltage can be significantly improved, the voltage sag or swell can be reduced, and the safe and stable operation of the grid can be guaranteed. According to the seasonal load characteristics, the energy storage charging and discharging strategy can be intelligently adjusted to ensure that the energy storage equipment provides effective support during peak load periods. Distributed energy storage inverters have fast response capabilities and can quickly adjust the output power to smooth out the voltage fluctuations caused by seasonal loads, thereby improving the response speed and regulation capabilities of the grid. In extreme weather or emergencies, distributed energy storage can be used as an emergency power supply to provide stable power supply for critical loads and enhance the resilience and reliability of the grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present invention 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 invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0052] Figure 1 The present invention is a flowchart of a method for suppressing voltage fluctuations of a distributed energy storage converter suitable for seasonal loads according to an embodiment of the present invention. DETAILED DESCRIPTION

[0053] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] like Figure 1 As shown, a method for suppressing voltage fluctuation of a distributed energy storage converter suitable for seasonal loads comprises:

[0055] Step 1: Identify the power grid management area, that is, the jurisdiction, and mark it as the target area; obtain the target area information map, including line distribution, power equipment, community, village, hospital and other related information; define the unit area according to the minimum power consumption area such as community, factory, office building, shopping mall, village, etc. The unit area is the minimum power consumption area; the definition and judgment can be combined with the corresponding line connection; identify the target area information map according to the unit area definition, and mark each unit area in the target area information map; obtain the historical power consumption data of each unit area and mark it as unit data; analyze the unit data to determine whether the corresponding unit area meets the seasonal load requirements, and mark the unit area that meets the seasonal load requirements as the seasonal unit area;

[0056] Seasonal load requirements are defined by managers based on actual management needs.

[0057] In one embodiment, whether the corresponding unit area meets the seasonal load requirement can be determined based on existing data determination technology or manually.

[0058] In one embodiment, the method for determining whether the corresponding unit area meets the seasonal load requirement includes:

[0059] Set seasonal load requirements and set seasonal judgment model according to seasonal load requirements. The seasonal judgment model is used to analyze the input data to determine whether it meets the seasonal requirements. The expression of the seasonal judgment model is: In the formula: s is the input data, the input data is the unit data; the output data is the seasonal judgment value PH(s);

[0060] The unit data of each unit area is analyzed through the seasonal judgment model to obtain the seasonal judgment value corresponding to each unit area; the unit area with a seasonal judgment value of 1 is marked as a seasonal unit area.

[0061] Step 2: Determine each energy storage control area according to each seasonal unit area, and set up energy storage equipment according to each energy storage control area;

[0062] For example, distributed energy storage converters and other related energy storage devices are set up in each energy storage control area for subsequent voltage suppression control based on the distributed energy storage converters.

[0063] In one embodiment, the energy storage control area can be set by existing methods such as manual methods.

[0064] In one embodiment, a method for setting an energy storage control area includes:

[0065] Step SA1: Acquire the performance data of the energy storage device, that is, the relevant data such as the corresponding adjustment range of the energy storage device during load adjustment, so as to determine the size of the area it can bear;

[0066] Step SA2: select any seasonal unit area as the initial area; obtain regional association data between the initial area and other seasonal unit areas, including seasonal unit areas corresponding to other initial areas, the regional association data including positional relationship, line connection relationship and other data between corresponding seasonal unit areas, used to determine whether the corresponding seasonal unit areas can be subjected to voltage suppression regulation through the same energy storage device, and set merging requirements according to whether voltage suppression regulation can be performed through the same energy storage device; evaluate whether the initial area and other seasonal unit areas meet the merging requirements,

[0067] Mark each seasonal unit area that meets the merging requirements as an area to be evaluated;

[0068] When there is no initial area, go to step SA7;

[0069] Step SA3: Combine the initial area with the corresponding area to be evaluated to form an initial combination, and combine in an arbitrary manner; analyze the initial combination through the performance data of the energy storage device to determine whether the historical power consumption data corresponding to the initial combination exceeds the performance requirements of the energy storage device, that is, exceeds the regulation upper limit; obtain the performance evaluation results, including whether the performance requirements are met or not;

[0070] When there is no area to be evaluated, the initial combination cannot be formed, step SA2;

[0071] Step SA4: when the performance evaluation result is that the performance requirement is not met, the corresponding initial combination is prohibited, that is, the initial area and the area to be evaluated corresponding to the initial combination will not appear subsequently; return to step SA3;

[0072] When the performance evaluation result is that the performance requirements are met, the corresponding initial combination is marked as a merged combination; the merged combination is combined with the corresponding area to be evaluated to form a new initial combination without repeated combinations; the new initial combination is analyzed through the performance data of the energy storage equipment to obtain the performance evaluation result, including whether the performance requirements are met or not;

[0073] Step SA5: when the performance evaluation result is that the performance requirement is not met, the corresponding initial combination is prohibited, and the combination mode corresponding to the corresponding merged combination is output, that is, the merged combination in the corresponding initial combination; and the process returns to step SA3;

[0074] When the performance evaluation result is that the performance requirements are met, the corresponding initial combination is marked as a new merged combination; the new merged combination is combined with the corresponding area to be evaluated to form a new initial combination; the new initial combination is analyzed through the performance data of the energy storage device to obtain a performance evaluation result, including whether the performance requirements are met or not;

[0075] Step SA6: Loop step SA5.

[0076] Step SA7: Identify the various combinations, each of which may correspond to a setting mode of an energy storage device; form various control schemes to be selected according to the various combinations, which are schemes formed by the combination of various combinations, equivalent to the layout scheme of the action area of ​​the energy storage device; the various combinations corresponding to the control scheme to be selected may not contain all seasonal unit areas, but the included combinations cannot be crossed, and crossing means that the corresponding multiple combinations in the control scheme to be selected have the same seasonal unit area; various control schemes to be selected may be determined according to the existing data arrangement method, such as the enumeration method may be used to determine the various control schemes to be selected;

[0077] Conduct control evaluation on each candidate control scheme to determine whether the corresponding candidate control scheme meets the regional control requirements. The regional control requirements are set by the management personnel according to the voltage suppression requirements of the target area; obtain the corresponding control evaluation results, including qualified control evaluation and unqualified control evaluation;

[0078] Step SA8: Mark the candidate control schemes merged by the control evaluation as the schemes to be applied. The subsequent management personnel determine the target application scheme according to the actual situation. The determination of the target application scheme needs to be determined based on various actual factors such as whether the energy storage setting is allowed in each seasonal unit area and cost considerations;

[0079] Identify the various combinations corresponding to the target application solutions, and integrate the seasonal unit areas corresponding to the combination methods into a storage control area.

[0080] In one implementation, the method of performing regulation evaluation on each candidate regulation scheme in step SA7 includes:

[0081] Setting scheme simulation data according to the historical electricity consumption data of the target area, that is, setting representative data as simulation data according to the historical electricity consumption data, for verifying and simulating each scheme, and simulating the corresponding voltage suppression effect after the scheme is applied;

[0082] The energy storage benchmark adjustment principle is set. The energy storage benchmark adjustment principle is to use the fast response characteristics of the distributed energy storage converter to charge in advance when the load is predicted to increase, and discharge when the load is predicted to decrease, so as to balance the instantaneous power difference of the power grid and suppress voltage fluctuations; that is, when the load is predicted to increase, charge within the preset time period; when the load is predicted to decrease, discharge within the preset time period. The specific preset time period is determined according to its charging and discharging performance to ensure that it meets the working requirements.

[0083] According to the energy storage benchmark adjustment principle and the scheme simulation data, each candidate control scheme is simulated to obtain the corresponding simulation verification data, that is, according to the energy storage benchmark adjustment principle, the power grid of the original target area is adjusted in combination with the candidate control scheme, and the voltage suppression after the adjustment is simulated and marked as simulation verification data, which is generally represented by load curves such as voltage and current, which is more intuitive;

[0084] Identify the voltage data corresponding to the simulation data of the scheme and mark it as the benchmark simulation result;

[0085] Compare the benchmark simulation results with each simulation verification data to determine the corresponding suppression effect ranking, so as to rank the magnitude of the impact of load fluctuations such as the voltage and current of the power grid, and the greater the effect, the higher the ranking; rank the candidate control schemes according to the suppression effect ranking to obtain the first sequence; obtain the voltage suppression target, which is set by the management personnel according to the needs and expectations, and is used to indicate that the suppression effect cannot be lower than a certain standard; remove the candidate control schemes that are lower than the voltage suppression target from the first sequence to obtain the second sequence;

[0086] According to the simulation process and simulation verification results, the vacancy rate corresponding to each candidate control scheme in the second sequence is counted. The vacancy rate is counted according to whether each energy storage device is used, the proportion of the performance used during use to its total performance, etc., that is, it is used to measure its resource utilization; each candidate control scheme with a vacancy rate lower than the threshold value X1 is eliminated from the second sequence to obtain a third sequence;

[0087] The regulatory assessment results of each candidate regulatory scheme in the third sequence are deemed to be qualified in the regulatory assessment;

[0088] The regulatory assessment results of each candidate regulatory scheme not in the third sequence shall be deemed as unqualified in the regulatory assessment.

[0089] Step 3: Setting a voltage suppression plan based on the preset energy storage benchmark adjustment principle and the energy storage equipment in each energy storage control area;

[0090] Based on the historical electricity consumption data, simulation tests are carried out to determine the best control method, that is, the setting of preset time periods, the judgment criteria for load increase / reduction, charging and discharging parameters and other related data; it is set up by professionals and implemented through expert demonstration.

[0091] Step 4: Establish a load forecasting model. The load forecasting model is established based on the historical load data of the power grid. It is used to predict the load change trend in the future according to various factors such as seasons and meteorological environment, that is, to predict load data for prediction and obtain load forecast data. Specifically, it is established using existing forecasting technology. For example, it is established based on neural networks such as DNN networks, and the corresponding training sets are established manually for training. The training set includes input data and output data. The input data is prediction condition data, which is various data related to load forecasting. The output data is load forecast data. The load forecasting model after successful training is analyzed.

[0092] Preset various collection items according to load condition data, perform real-time data collection according to various preset collection items, obtain load condition data, analyze the load condition data through a load forecasting model, and obtain corresponding load forecast data;

[0093] Step 5: Analyze the load forecast data according to the voltage suppression scheme, obtain the control instructions of each energy storage device, and control each energy storage device according to the control instructions to balance the instantaneous power difference of the power grid, thereby suppressing voltage fluctuations.

[0094] By optimizing the control strategy of distributed energy storage inverters, the voltage fluctuations caused by seasonal load changes can be effectively suppressed, the stability of the grid voltage can be significantly improved, the voltage sag or swell can be reduced, and the safe and stable operation of the grid can be guaranteed. According to the seasonal load characteristics, the energy storage charging and discharging strategy can be intelligently adjusted to ensure that the energy storage equipment provides effective support during peak load periods. Distributed energy storage inverters have fast response capabilities and can quickly adjust the output power to smooth out the voltage fluctuations caused by seasonal loads, thereby improving the response speed and regulation capabilities of the grid. In extreme weather or emergencies, distributed energy storage can be used as an emergency power supply to provide stable power supply for critical loads and enhance the resilience and reliability of the grid.

[0095] The present application also provides an embodiment corresponding to a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps described in the above embodiment of a method for suppressing voltage fluctuations of a distributed energy storage converter applicable to seasonal loads are implemented.

[0096] It is understandable that if the method in the above embodiment is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program code.

[0097] The above formulas are all calculated by removing dimensions and taking numerical values. The formula is a formula that is closest to the actual situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained by simulating a large amount of data.

[0098] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0099] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, is also included in the patent protection scope of the present invention.

[0100] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

[0101] For the convenience of description, the above device is described by dividing each unit into functions and describing them separately. Of course, when implementing the present application, the functions of each unit can be implemented in the same one or more software and / or hardware. It should be understood by those skilled in the art that the embodiments of the present invention can be provided as methods, systems or computer program products. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention can take 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.

[0102] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 The functionality specified in one or more boxes.

[0103] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A function specified in a process or multiple boxes.

[0104] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

Claims

1. A method for suppressing voltage fluctuations of a distributed energy storage converter suitable for seasonal loads, characterized in that: The steps include: Step 1: Mark the target area, obtain the target area information map, and set each seasonal unit area according to the target area information map; the seasonal unit area is the power consumption area that meets the seasonal load requirements; Step 2: Determine each energy storage control area according to each seasonal unit area, and set up energy storage equipment according to each energy storage control area; Step 3: Setting a voltage suppression plan based on the preset energy storage benchmark adjustment principle and the energy storage equipment in each energy storage control area; Step 4: Establish a load forecasting model, collect real-time data according to preset collection items, obtain load condition data, analyze the load condition data through the load forecasting model, and obtain load forecast data; Step 5: Analyze the load forecast data according to the voltage suppression scheme, obtain the control instructions of each energy storage device, and control each energy storage device according to the control instructions.

2. A method for suppressing voltage fluctuations of a distributed energy storage converter suitable for seasonal loads according to claim 1, characterized in that: The step of setting each seasonal unit area according to the target area information map includes: Setting a unit area definition, identifying the target area information map according to the unit area definition, and marking each unit area in the target area information map according to the identification result; obtaining historical power consumption data of each unit area and marking it as unit data; Setting seasonal load requirements, and setting a seasonality determination model according to the seasonal load requirements; Analyze the unit data of each unit area by using the seasonal judgment model to obtain a seasonal judgment value corresponding to each unit area; the seasonal judgment value is 1 or 0; Each unit area having a seasonal judgment value of 1 is marked as a seasonal unit area.

3. A method for suppressing voltage fluctuations of a distributed energy storage converter suitable for seasonal loads according to claim 2, characterized in that: The expression of the seasonality judgment model is: In the formula: s is the input data, the input data is the unit data; the output data is the seasonal judgment value PH(s).

4. The method for suppressing voltage fluctuation of a distributed energy storage converter suitable for seasonal loads according to claim 1, characterized in that: The method for setting the energy storage control area includes: Step SA1: Obtaining energy storage device performance data; Step SA2: select any seasonal unit area as the initial area; if there is no initial area, proceed to step SA7; Acquire regional association data between the initial region and each seasonal unit region; set merging requirements; According to the corresponding regional association data, it is evaluated whether the initial region and each seasonal unit region meet the merging requirements, and each seasonal unit region that meets the merging requirements is marked as the region to be evaluated of the initial region; Step SA3: combining the initial area with the corresponding area to be evaluated to form an initial combination; when there is no area to be evaluated, step SA2; Analyzing the initial combination through energy storage device performance data to obtain a performance evaluation result, wherein the performance evaluation result includes whether the performance requirements are met or not met; Step SA4: When the performance evaluation result is that the performance requirement is not met, the corresponding initial combination is prohibited; and the process returns to step SA3; When the performance evaluation result satisfies the performance requirements, the initial combination is marked as a combined combination; the combined combination is combined with the corresponding area to be evaluated to form a new initial combination; the initial combination is analyzed through the energy storage device performance data to obtain a new performance evaluation result; Step SA5: When the performance evaluation result is that the performance requirement is not met, the corresponding initial combination is prohibited, the combination mode corresponding to the corresponding merged combination is output, and the process returns to step SA3; When the performance evaluation result satisfies the performance requirements, the corresponding initial combination is marked as a new combined combination; the new combined combination is combined with the corresponding area to be evaluated to form a new initial combination; the initial combination is analyzed through the energy storage device performance data to obtain a new performance evaluation result; Step SA6: loop step SA5; Step SA7: identifying various combinations, and forming various control schemes to be selected according to the various combinations; Performing a control evaluation on each of the selected control schemes to obtain a corresponding control evaluation result, wherein the control evaluation result includes a control evaluation qualified and a control evaluation unqualified; Step SA8: Marking each of the candidate control schemes merged by the control evaluation as a to-be-applied scheme, and determining a target application scheme from each of the to-be-applied schemes; Identify the various combination methods corresponding to the target application solutions, and integrate the seasonal unit areas corresponding to the combination methods into an energy storage control area.

5. A method for suppressing voltage fluctuations of a distributed energy storage converter suitable for seasonal loads according to claim 4, characterized in that: The method of evaluating each candidate control scheme in step SA7 includes: Set simulation data for the scheme based on historical electricity consumption data of the target area; set energy storage benchmark adjustment principles; Simulate each candidate control scheme according to the energy storage benchmark adjustment principle and scheme simulation data to obtain corresponding simulation verification data; identify the benchmark simulation results corresponding to the scheme simulation data; Compare the benchmark simulation results with each simulation verification data, determine the inhibition effect ranking corresponding to each simulation verification data, and rank each candidate control scheme according to the inhibition effect ranking to obtain a first sequence; Obtaining a voltage suppression target, eliminating each candidate control scheme that is lower than the voltage suppression target from the first sequence, and obtaining a second sequence; Counting the vacancy rates corresponding to the candidate control schemes in the second sequence, and removing the candidate control schemes with vacancy rates lower than the threshold value X1 from the second sequence, to obtain a third sequence; The regulatory assessment results of each candidate regulatory scheme in the third sequence are deemed to be qualified in the regulatory assessment; The regulatory assessment results of each candidate regulatory scheme not in the third sequence shall be deemed as unqualified in the regulatory assessment.

6. A method for suppressing voltage fluctuations of a distributed energy storage converter suitable for seasonal loads according to claim 5, characterized in that: The energy storage benchmark adjustment principle is: when the predicted load increases, charging is performed within a preset time period; when the predicted load decreases, discharging is performed within a preset time period.

7. The method for suppressing voltage fluctuation of a distributed energy storage converter suitable for seasonal loads according to claim 1, characterized in that: The load forecasting model is established based on a deep neural network, the input data is load condition data, and the output data is load forecast data.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for suppressing voltage fluctuations of a distributed energy storage converter suitable for seasonal loads according to any one of claims 1 to 7 is implemented.

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