Black start method and device of optical storage micro-grid and electronic equipment

Abstract

The present application relates to the technical field of micro-grid control, and discloses a black start method and device of a light-storage micro-grid and an electronic device, the method comprising: obtaining a photovoltaic predicted power and a load predicted power issued by cloud AI; determining whether an automatic black start condition is met based on the photovoltaic predicted power and the load predicted power; when the automatic black start condition is met, controlling an energy storage converter to perform automatic black start; after detecting that the energy storage converter successfully performs automatic black start, controlling a photovoltaic inverter to start to restore power supply of the light-storage system. By obtaining the photovoltaic predicted power and the load predicted power issued by cloud AI, it is automatically determined whether the black start condition is met, without the need for manual on-site operation or remote manual intervention, thereby avoiding the problem of recovery delay caused by reliance on personnel response.

Description

Technical Field

[0001] This invention relates to the field of microgrid control technology, specifically to a black-start method, apparatus, and electronic equipment for photovoltaic-storage microgrids. Background Technology

[0002] When existing photovoltaic-storage microgrids shut down due to lack of sunlight while operating off-grid, power restoration typically relies on on-site operation by maintenance personnel or manual clicking of the black start button via remote data acquisition interface. This manual method requires manual assessment of whether the current photovoltaic power is sufficient to support system startup. However, personnel can only make decisions based on instantaneous data, lacking the ability to predict real-time photovoltaic power output or whether future sunlight will be sufficient to maintain system energy balance. This not only leads to slow response times and missed optimal recovery windows but also risks inaccurate photovoltaic power output predictions, resulting in over-discharge of energy storage and subsequent system shutdowns due to insufficient energy after startup, impacting power supply reliability and system stability. Summary of the Invention

[0003] This invention provides a black start method, device, and electronic equipment for photovoltaic-storage microgrids to solve the problems of existing photovoltaic-storage microgrids relying on manual judgment for power restoration after off-grid operation, slow response, and easy secondary shutdowns due to insufficient photovoltaic energy.

[0004] In a first aspect, the present invention provides a black-start method for a photovoltaic-storage microgrid, the photovoltaic-storage microgrid including a photovoltaic-storage system, an energy storage converter, and a photovoltaic inverter, the method comprising: Obtain photovoltaic power forecasts and load forecasts from cloud-based AI; Based on the photovoltaic power forecast and the load forecast, determine whether the automatic black start conditions are met; When the automatic black start conditions are met, the energy storage converter is controlled to perform an automatic black start. After detecting that the energy storage converter has successfully performed an automatic black start, the photovoltaic inverter is controlled to start in order to restore power supply to the photovoltaic-energy storage system.

[0005] This invention provides a black start method for a photovoltaic-storage microgrid. By acquiring the predicted photovoltaic power and load power from cloud-based AI, it automatically determines whether the black start conditions are met, eliminating the need for on-site manual operation or remote manual intervention. This avoids the recovery delay problem caused by reliance on human response. Furthermore, by making condition judgments based on the predicted data, it can predict whether the photovoltaic energy is sufficient to support system operation before startup, preventing excessive discharge of energy storage due to insufficient photovoltaic power and secondary shutdowns after system startup. This improves the success rate of black start and the reliability of system power restoration, solving the problems of existing photovoltaic-storage microgrids relying on manual judgment for power restoration after off-grid operation, slow response, and susceptibility to secondary shutdowns due to insufficient photovoltaic energy.

[0006] In one alternative implementation, the acquisition of the photovoltaic power prediction and load prediction power issued by cloud AI is performed after the microgrid is off-grid and the energy storage state of charge is lower than the off-grid discharge cutoff charge, causing the photovoltaic and energy storage system to shut down.

[0007] In the above technical solution, the step of obtaining cloud AI predicted power is triggered only after the photovoltaic and energy storage system shuts down due to the off-grid operation of the microgrid and the energy storage state of charge being lower than the off-grid discharge cutoff charge. This ensures that the method is only activated when the photovoltaic and energy storage system actually needs to restore power, avoiding unnecessary calculations and resource occupation during the normal operation of the photovoltaic and energy storage system, reducing the processing burden of the controller, and making the black start triggering time accurately correspond to the actual power loss state of the photovoltaic and energy storage system, thus improving the start accuracy and execution efficiency of the automatic black start process.

[0008] In one optional implementation, determining whether the automatic black-start conditions are met based on the photovoltaic predicted power and the load predicted power includes: Determine if automatic black boot is enabled; if not, wait for manual black boot. Determine whether the current state of charge of the energy storage is greater than the preset minimum state of charge threshold; If the minimum voltage enable is turned on, the DC voltage of each photovoltaic inverter is collected, the proportion of the total rated power of photovoltaic inverters that meet the minimum voltage condition to the total rated power of all photovoltaic inverters is calculated, and the photovoltaic predicted power at each time point in the future time period is updated using the proportion. Determine whether the updated photovoltaic power forecast is greater than or equal to the load forecast power at all points in the future time period. If the minimum power enable is turned on, it is determined whether the refreshed photovoltaic predicted power is greater than or equal to the preset minimum power threshold at each time point in the future time period. When all the above conditions are met and the preset duration is satisfied, the automatic black start process is triggered.

[0009] The above technical solution establishes a multi-level, configurable automatic black-start criterion system by sequentially judging automatic black-start enable, energy storage state of charge, comparison between the DC voltage-corrected photovoltaic predicted power and the load predicted power, and comparison between the photovoltaic predicted power and the minimum power threshold. Black start is only triggered after all the above conditions have been continuously met for a preset time. Specifically, using the DC voltage of the photovoltaic inverter to correct the AI ​​predicted power eliminates prediction deviations caused by insufficient voltage in some inverters, making the power judgment closer to the actual power generation capacity on site. Simultaneously, requiring the photovoltaic predicted power to continuously cover the load predicted power and the minimum power threshold effectively avoids false starts caused by short-term photovoltaic fluctuations, preventing the system from shutting down again due to insufficient energy after startup, significantly improving the triggering accuracy of automatic black start and the operational stability after system recovery.

[0010] In one optional implementation, determining whether the automatic black start condition is met further includes: If the predicted photovoltaic power and load power for the future time period are not matched by cloud AI, the automatic black start process will not be triggered.

[0011] In the above technical solution, by prohibiting the triggering of the automatic black start process when the photovoltaic predicted power and load predicted power are not matched by cloud AI, it is possible to avoid blindly starting the photovoltaic and energy storage system under the condition of lack of effective prediction data, prevent incorrect judgment of whether the photovoltaic energy is sufficient due to data loss, thereby reducing the risk of the photovoltaic and energy storage system shutting down again due to insufficient actual power generation capacity after startup, and improving the safety and reliability of the automatic black start process.

[0012] In one optional implementation, the formula for calculating the refreshed photovoltaic power prediction is: The updated photovoltaic power forecast = photovoltaic power forecast at a certain time point × (total rated power of photovoltaic inverters that meet the minimum voltage condition / total rated power of all photovoltaic inverters).

[0013] In one alternative implementation, controlling the energy storage converter to perform an automatic black start includes: Send an automatic black start command to the energy storage converter; Obtain the state of charge (SOC) of the battery corresponding to the energy storage converter. If the SOC is greater than or equal to a preset percentage, control the energy storage converter to perform automatic black start; otherwise, do not perform automatic black start.

[0014] In the above technical solution, after issuing an automatic black start command to the energy storage converter, its state of charge is further obtained and compared with a preset percentage. Automatic black start is only executed when the state of charge meets the conditions; otherwise, it is not executed. This avoids forced start when the corresponding battery of the energy storage converter is underpowered, preventing black start failure or secondary shutdown of the photovoltaic-energy storage system due to the energy storage converter's inability to maintain voltage stability. This improves the success rate of the automatic black start process and the reliability of system recovery.

[0015] In one alternative implementation, controlling the energy storage converter to perform an automatic black start further includes: If the energy storage converter is not detected to have successfully performed an automatic black start within the preset timeout period, the automatic black start is deemed to have failed.

[0016] In the above technical solution, if the automatic black start is not detected to have been successfully executed by the energy storage converter within a preset timeout period, the automatic black start failure is determined. This can terminate the abnormal black start process in a timely manner, avoid the control process from falling into an infinite waiting state due to the energy storage converter's inability to start normally for a long time, prevent the controller resources from being ineffectively occupied, and provide a clear failure judgment basis for subsequent re-attempts of black start or manual intervention, thereby improving the integrity and controllability of the automatic black start process.

[0017] In one optional implementation, after detecting that the energy storage converter has successfully performed an automatic black start, the photovoltaic inverter is controlled to start, including: First, start up the photovoltaic inverters that meet the minimum voltage condition in batches, and then start up the photovoltaic inverters that do not meet the minimum voltage condition one by one; meeting the minimum voltage condition means that the DC voltage of the photovoltaic inverter is greater than or equal to the preset automatic black start minimum voltage.

[0018] In the above technical solution, by first starting up photovoltaic inverters that meet the minimum voltage conditions in batches, and then starting up photovoltaic inverters that do not meet the minimum voltage conditions one by one, the inverters with normal power generation capacity can be restored first, and the power supply capacity of the photovoltaic-storage system can be quickly established. At the same time, by starting up the inverters with insufficient voltage one by one, the current surge caused to the photovoltaic-storage system by starting up too many inverters with abnormal voltage at one time is avoided, the regulation burden of the energy storage converter and the risk of voltage instability of the photovoltaic-storage system are reduced, and the stability and safety of the photovoltaic-storage system power supply restoration after black start are improved.

[0019] In a second aspect, the present invention provides a black-start device for a photovoltaic-storage microgrid, the photovoltaic-storage microgrid including a photovoltaic-storage system, an energy storage converter, and a photovoltaic inverter, the device comprising: The predicted power acquisition module is used to acquire the photovoltaic predicted power and load predicted power issued by cloud AI. The automatic black start condition judgment module is used to determine whether the automatic black start conditions are met based on the photovoltaic predicted power and the load predicted power. The automatic black start execution module is used to control the energy storage converter to perform automatic black start when the automatic black start conditions are met. The photovoltaic inverter start-up control module is used to control the photovoltaic inverter to start after detecting that the energy storage converter has successfully performed an automatic black start, so as to restore the power supply of the photovoltaic-energy storage system.

[0020] Thirdly, the present invention provides an electronic device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the black-start method of the photovoltaic-storage microgrid described in the first aspect or any corresponding embodiment thereof.

[0021] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the black-start method of the photovoltaic-storage microgrid described in the first aspect or any corresponding embodiment thereof.

[0022] Fifthly, the present invention provides a computer program product, including computer instructions, which are used to cause a computer to execute the black-start method of the photovoltaic-storage microgrid of the first aspect or any corresponding embodiment described above. Attached Figure Description

[0023] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0024] Figure 1 This is a schematic diagram of the workflow of an application scenario according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the first process of a black start method for a photovoltaic-storage microgrid according to an embodiment of the present invention. Figure 3 This is a schematic diagram of the second process of the black start method for a photovoltaic-storage microgrid according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the third process of the black start method for a photovoltaic-storage microgrid according to an embodiment of the present invention; Figure 5 This is a structural block diagram of a black-start device for a photovoltaic-storage microgrid according to an embodiment of the present invention; Figure 6 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0027] As an optional application scenario of this invention, a microgrid solution scenario is provided. This microgrid is a photovoltaic-storage microgrid, which includes a data acquisition controller (SEC3000C), an energy storage converter, a photovoltaic inverter, an STS (Static Transfer Switch) cabinet, and a generator. The microgrid's operating conditions mainly include grid-connected operation, off-grid operation, grid-connected to off-grid switching, and off-grid to grid-connected switching.

[0028] The STS switching cabinet communicates with the data acquisition controller and the energy storage PCS (Power Conversion System) to achieve grid-to-offline switching, enabling the system to switch to off-grid operation. Off-grid control operation ensures the continuity of power supply to critical loads.

[0029] like Figure 1 The diagram shown illustrates the black start process of a photovoltaic-storage microgrid. The workflow is as follows: 1. In the control strategy → microgrid control → black start parameter setting page of the data acquisition controller (SEC3000C), the user configures the automatic black start control parameters and enables the automatic black start function.

[0030] 2. The cloud-based AI is trained and predicted based on weather data, historical photovoltaic power data of subarrays, historical load power data of subarrays, and site operation and maintenance data to generate photovoltaic power generation data and load power data for the next day or hour, and then sends them to the data acquisition controller (SEC3000C).

[0031] 3. When the microgrid is in off-grid operation, if the real-time state of charge of the energy storage is lower than the off-grid discharge cutoff state of charge, the photovoltaic-storage system will automatically shut down and resume power supply operation through the black start function after the sunlight is restored.

[0032] 4. After sunlight resumes the next day, the data acquisition controller (SEC3000C) determines whether the automatic black start conditions are met based on the following data: The cloud-based AI-generated photovoltaic power forecast, load forecast, energy storage parameters (state of charge, etc.), DC voltage of the photovoltaic inverter, and user-configured automatic black start parameters are all included.

[0033] 5. When the automatic black start conditions are met, the data acquisition controller (SEC3000C) performs a black start operation: Black start preparation for energy storage converter: The data acquisition controller sends a black start preparation command to the energy storage converter; Voltage establishment command issued: The data acquisition controller issues a black start voltage establishment command to the energy storage converter; Waiting for AC voltage to establish: The data acquisition controller waits for the microgrid's AC voltage to establish; Periodic query of AC voltage: The data acquisition controller periodically queries the AC voltage status of the energy storage converter to determine whether the AC voltage has been successfully established.

[0034] 6. Successful Black Start: If the AC voltage is successfully established, the data acquisition controller sends start-up commands to the photovoltaic inverters in batches, and the photovoltaic and energy storage system in the microgrid resumes power supply operation; Black start failure: If the AC voltage is not successfully established within the timeout period, the data acquisition controller will generate a black start failure alarm.

[0035] For example, off-grid control in microgrid scenarios is divided into photovoltaic-storage-oil scenarios and photovoltaic-storage-removal scenarios.

[0036] I. In a photovoltaic-storage-oil scenario, the photovoltaic-storage system prioritizes power supply to minimize diesel consumption. When the power supply from the photovoltaic-storage system is insufficient, the diesel generator provides supplementary power. The workflow is as follows: 1. When the microgrid is in off-grid operation and the energy storage charge is low, the microgrid controller starts the diesel generator, which acts as a voltage source to carry the load, and the energy storage converter switches to grid-connected mode. 2. When the diesel generator is running under load and the energy storage is charged to a high state of charge, the microgrid controller will shut down the diesel generator and the energy storage converter will become the main power source to run under load. 3. When the diesel generator is running with the photovoltaic and energy storage system, the microgrid controller controls the output power of the photovoltaic system and the energy storage converter to maintain the output power of the diesel generator at no less than 30% of its rated power, thus maintaining economical operation.

[0037] II. In the scenario of removing excess oil from the photovoltaic-storage system, the photovoltaic-storage system supplies power to the microgrid loads to ensure the continuity of power supply to the microgrid. The workflow is as follows: 1. When the photovoltaic and energy storage system has insufficient power but the photovoltaic system has sufficient power, the photovoltaic system charges the energy storage system (limiting the photovoltaic power generation if necessary). When the photovoltaic system is insufficient, the photovoltaic and energy storage system supplies power to the load. 2. Once the energy storage is fully charged, the photovoltaic system stops outputting power, or it controls repeated charging within the 3% dead zone of the energy storage's state of charge. 3. During energy storage discharge, the load is powered by the photovoltaic energy storage system or solely by the energy storage system; 4. When the energy storage is discharging, the microgrid controller manages the load according to the energy storage state of charge, performs load shedding operations, the load switch is opened, and the microgrid system operates under reduced load; 5. When the energy storage state of charge is too low, the photovoltaic-storage system will shut down and wait for the sunlight to recover before restarting. 6. After sunlight is restored, the microgrid is started through the black start function, and the photovoltaic and energy storage system in the microgrid is powered on and put into operation.

[0038] Black boot scenarios are divided into manual black boot and automatic black boot: When it is a manual black start, the operator can manually click the black start button on the data acquisition controller interface to start the microgrid.

[0039] When automatic black start is enabled, in the absence of a diesel generator, the photovoltaic and energy storage system will automatically perform a black start the next day when sunlight resumes after the system is shut down at night, thus powering up and operating the photovoltaic and energy storage system within the microgrid.

[0040] The existing SEC3000C data acquisition controller interface provides a manual one-button black start button, but does not support automatic black start for microgrids. In the automatic black start scheme, the relevant technology relies on the subarray's total inverter to estimate the power, but currently photovoltaic inverters do not have the ability to estimate the power based on sunlight. The automatic black start criterion can only use DC voltage judgment, which poses a risk of unreliability.

[0041] Therefore, this invention provides a black start method for a photovoltaic-storage microgrid, which utilizes cloud-based AI photovoltaic prediction capabilities to enhance the intelligent identification of automatic black start, eliminating the need for on-site manual operation or remote manual intervention, thereby avoiding the recovery delay problem caused by reliance on human response.

[0042] According to an embodiment of the present invention, a black start method for a photovoltaic-storage microgrid is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0043] This embodiment provides a black-start method for a photovoltaic-storage microgrid, which can be used in photovoltaic-storage microgrids, including a photovoltaic-storage system, an energy storage converter, and a photovoltaic inverter. Figure 2 This is a flowchart of a black-start method for a photovoltaic-storage microgrid according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps: Step S201: Obtain the photovoltaic power forecast and load forecast power issued by the cloud AI.

[0044] Among them, cloud AI is a prediction model that runs in the cloud. It uses machine learning or deep learning algorithms to train based on various historical data to generate photovoltaic power generation prediction data (referred to as photovoltaic predicted power) and load power prediction data (referred to as load predicted power) for future time periods. It then sends the data to the data acquisition controller (SEC3000C) via the MQTT (Message Queuing Telemetry Transport) protocol.

[0045] Step S202: Based on the photovoltaic predicted power and the load predicted power, determine whether the automatic black start conditions are met.

[0046] Automatic black start refers to the process where, after the microgrid is off-grid and the photovoltaic-storage system automatically shuts down due to low energy storage charge, the data acquisition controller automatically determines whether the start-up conditions are met based on data such as photovoltaic power and load power predicted by cloud AI, and automatically restores power supply to the photovoltaic-storage system when the conditions are met, without manual intervention.

[0047] The automatic black start condition is a comprehensive judgment system composed of multiple sub-conditions. The data acquisition controller will trigger the automatic black start process only when all sub-conditions are met.

[0048] Automatic black boot conditions include: 1. Enabling condition: Automatic black start enable switch is turned on; 2. Energy storage state of charge condition: The current energy storage state of charge is greater than the preset minimum state of charge threshold; 3. AI Prediction Data Matching Conditions: Able to match datasets of photovoltaic power prediction and load prediction for future time periods predicted by cloud-based AI; 4. Photovoltaic power coverage load condition: The updated photovoltaic power forecast is greater than or equal to the load forecast power at all points in time during the future period; 5. Photovoltaic power coverage minimum power condition: If the minimum power enable is turned on, the refreshed photovoltaic predicted power will be greater than or equal to the preset minimum power threshold at each time point in the future time period. 6. Duration condition: The above conditions (2 to 5) are continuously satisfied for the preset duration.

[0049] Step S203: When the automatic black start conditions are met, control the energy storage converter to perform automatic black start.

[0050] Specifically, when the automatic black start conditions are met, the data acquisition controller sends a start command to the energy storage converter. The energy storage converter operates in voltage source mode, establishing a stable AC voltage on the microgrid bus, providing voltage support for the subsequent connection of photovoltaic inverters and power restoration.

[0051] Step S204: After detecting that the energy storage converter has successfully performed automatic black start, control the photovoltaic inverter to start up in order to restore the power supply of the photovoltaic-energy storage system.

[0052] Specifically, after detecting that the energy storage converter has successfully established AC voltage, the data acquisition controller first starts up the photovoltaic inverters whose DC voltage has reached the standard in batches to quickly restore the main power generation capacity, and then starts up the remaining photovoltaic inverters one by one to ensure that the power supply of the photovoltaic-energy storage system bus is restored smoothly.

[0053] The black-start method for photovoltaic-storage microgrids provided in this embodiment automatically determines whether the black-start conditions are met by acquiring the photovoltaic predicted power and load predicted power issued by cloud AI. This eliminates the need for manual on-site operation or remote manual intervention, thus avoiding the recovery delay problem caused by reliance on human response. At the same time, by making condition judgments based on the predicted data, it can predict whether the photovoltaic energy is sufficient to support the system operation before startup, preventing excessive discharge of energy storage due to insufficient photovoltaic power and secondary shutdown after system startup. This improves the success rate of black-start and the reliability of system power restoration, and solves the problems of existing photovoltaic-storage microgrids relying on manual judgment for power restoration after off-grid operation, slow response, and easy secondary shutdown due to insufficient photovoltaic energy.

[0054] This embodiment provides a black-start method for a photovoltaic-storage microgrid, which can be used in photovoltaic-storage microgrids, including a photovoltaic-storage system, an energy storage converter, and a photovoltaic inverter. Figure 3 This is a flowchart of a black-start method for a photovoltaic-storage microgrid according to an embodiment of the present invention, such as... Figure 3 As shown, the process includes the following steps: Step S301: Obtain the photovoltaic power forecast and load forecast power issued by the cloud AI.

[0055] Specifically, the acquisition of photovoltaic power prediction and load prediction power issued by cloud AI is performed after the microgrid is off-grid and the energy storage state of charge is lower than the off-grid discharge cutoff charge, causing the photovoltaic and energy storage system to shut down.

[0056] (1) First, the data acquisition controller provides automatic black start parameter configuration, including: Automatic black start basic parameters: automatic black start enable switch and automatic black start minimum state of charge (SOC) threshold; Automatic Black Start Advanced Parameters: Automatic Black Start Minimum Power Enable Switch, Automatic Black Start Minimum Power Setting Value, Automatic Black Start Minimum Voltage Enable Switch, Automatic Black Start Minimum Voltage Setting Value.

[0057] (2) The cloud AI sends the photovoltaic power prediction and load prediction to the data acquisition controller through the MQTT protocol. The data acquisition controller receives the prediction data and saves it locally.

[0058] (3) When the microgrid is in off-grid operation, the lack of sunlight causes the photovoltaic system to be unable to generate electricity, and the energy storage system discharges to supply power to the load. When the real-time charge state of the energy storage system drops below the off-grid discharge cutoff charge state, the data acquisition controller controls the photovoltaic-storage system to shut down and waits for the sunlight to recover before restoring power supply through the black start function.

[0059] Step S302: Based on the photovoltaic predicted power and the load predicted power, determine whether the automatic black start conditions are met.

[0060] Specifically, upon restoration of illumination, the data acquisition controller automatically performs a black start to restore power, and the execution process is as follows: Step S302 above includes: Step S3021: Determine whether automatic black boot is enabled. If not, wait for manual black boot.

[0061] Specifically, the data acquisition controller periodically checks the automatic black start enable switch. Enable auto_blackstart Is it enabled? If not enabled, wait for the user to perform a manual black boot operation. If enabled, proceed to the next step.

[0062] Step S3022: Determine whether the current energy storage state of charge is greater than the preset minimum state of charge threshold.

[0063] Specifically, the data acquisition controller determines the real-time state of charge of energy storage in the microgrid. Soc current Is it greater than the minimum state of charge threshold for automatic black start? Soc blackstart_min If the conditions are not met, the automatic black boot process will not be triggered; if the conditions are met, proceed to the next step.

[0064] In step S3023, if the predicted photovoltaic power and predicted load power for the future time period are not matched by cloud AI, the automatic black start process will not be triggered.

[0065] Specifically, the data acquisition controller matches the current time with a dataset of predicted photovoltaic power and load power for a future time period predicted by cloud-based AI. The time span of this dataset is t minutes forward from the current time, where t can be 2 minutes or set according to actual needs. The purpose is to minimize the risk of the photovoltaic and energy storage system shutting down again due to insufficient photovoltaic power after startup. If no AI prediction dataset is found, the automatic black start process is not triggered; if a match is successful, the process proceeds to the next step.

[0066] Step S3024: If the minimum voltage enable is turned on, the DC voltage of each photovoltaic inverter is collected, the proportion of the total rated power of the photovoltaic inverters that meet the minimum voltage condition to the total rated power of all photovoltaic inverters is calculated, and the photovoltaic predicted power at each time point in the future time period is updated using the proportion.

[0067] Specifically, if the automatic black start minimum voltage enable switch is enabled... Enable auto_blackstart_min_voltage It is now enabled. The data acquisition controller is traversing each photovoltaic inverter in the microgrid and calculating the DC voltage of each photovoltaic inverter. Voltage pv_dc_i and automatic black start minimum voltage Voltage blackstart_minThe difference is recorded separately for grid-connected photovoltaic inverters that meet the minimum voltage requirement for automatic black start and those that do not. Then, the rated power of all photovoltaic inverters is summed to obtain the total rated power of the photovoltaic inverters. P pv_rated_total The total rated power of grid-connected photovoltaic inverters that meet the minimum voltage requirements for automatic black start is the total rated power of photovoltaic inverters with normal voltage. P pv_rated_total_normal_voltage Refresh the calculation dataset to calculate the predicted power of photovoltaic power for each time span. P pv_pre_i_new The photovoltaic power forecast for each time point within the future time period will be updated according to the following formula: The updated photovoltaic (PV) predicted power = PV predicted power at a certain point in time × (total rated power of PV inverters meeting the minimum voltage condition / total rated power of all PV inverters), that is: P pv_pre_i_new =P pv_pre_i × (P pv_rated_total_normal_voltage / P pv_rated_total ) .

[0068] in, P pv_pre_i_new This is the updated photovoltaic power forecast. P pv_pre_i The original photovoltaic power forecast at a certain point in time. P pv_rated_total_normal_voltage To meet the minimum voltage requirements for the total rated power of photovoltaic inverters, P pv_rated_total The total rated power of all photovoltaic inverters.

[0069] The updated predicted power is more reliable than the original predicted power.

[0070] Step S3025: Determine whether the refreshed photovoltaic predicted power is greater than or equal to the load predicted power at each time point in the future time period.

[0071] Specifically, the data acquisition controller calculates the photovoltaic power prediction at each time point within the time span of the dataset. P pv_pre_i_new and load prediction power P load_pre_i If the difference is less than 0, it indicates that the photovoltaic predicted power cannot continuously cover the load predicted power, and the automatic black start process will not be triggered; if the difference is not less than 0 at all time points, proceed to the next step.

[0072] If the automatic black start minimum power enable switch is not turned on, proceed to step S3027; otherwise, proceed to the next step.

[0073] Step S3026: If the minimum power enable is turned on, determine whether the refreshed photovoltaic predicted power is greater than or equal to the preset minimum power threshold at each time point in the future time period.

[0074] The data acquisition controller calculates the photovoltaic power prediction after updating the dataset at each time point within the time span. P pv_pre_i_new With automatic black start minimum power P black_start_min The difference is calculated. If there is a difference less than 0, it indicates that the photovoltaic predicted power cannot continuously cover the minimum power for automatic black start, and the automatic black start process will not be triggered; if the difference at all time points is not less than 0, proceed to the next step.

[0075] Step S3027: When all the above conditions are met and the preset duration is satisfied, the automatic black start process is triggered.

[0076] If all the conditions in steps S3022 to S3026 above are met, then the step of controlling the energy storage converter to perform automatic black start when the automatic black start condition is met can continue to be executed.

[0077] Step S303: When the automatic black start conditions are met, control the energy storage converter to perform automatic black start.

[0078] Specifically, step S303 includes: Step S3031: Send an automatic black start command to the energy storage converter; obtain the state of charge of the battery corresponding to the energy storage converter. If the state of charge is greater than or equal to a preset percentage, control the energy storage converter to perform automatic black start; otherwise, do not perform automatic black start.

[0079] Specifically, the data acquisition controller sends an off-grid black start setting command to the energy storage converter. The energy storage converter determines whether the state of charge (SBC) of the corresponding battery meets the black start requirements (based on the energy storage converter's own data, requiring an SBC greater than or equal to 5%). If it meets the requirements, the energy storage converter performs an automatic black start; otherwise, it cannot perform an automatic black start.

[0080] Step S3032: If the energy storage converter is not detected to have successfully performed automatic black start within the preset timeout period, the automatic black start is determined to have failed.

[0081] Specifically, if the energy storage converter host is not detected to be running successfully within the 5-minute timeout period, the automatic black start is deemed to have failed.

[0082] Step S304: After detecting that the energy storage converter has successfully performed automatic black start, control the photovoltaic inverter to start.

[0083] Specifically, step S304 includes: Step a: First, start up the photovoltaic inverters that meet the minimum voltage condition in batches, and then start up the photovoltaic inverters that do not meet the minimum voltage condition one by one; meeting the minimum voltage condition means that the DC voltage of the photovoltaic inverter is greater than or equal to the preset automatic black start minimum voltage.

[0084] The data acquisition controller periodically queries the operating status of the energy storage converter main unit to determine whether it has successfully started. If the energy storage converter main unit is running, it sends start-up commands in batches to the photovoltaic inverters that meet the minimum voltage conditions for automatic black start, and the black start is successful.

[0085] For photovoltaic inverters that do not meet the minimum voltage requirements for automatic black start, the data acquisition controller issues start-up commands one by one to avoid impacting the microgrid by starting all of them at once.

[0086] The black-start method for a photovoltaic-storage microgrid provided in this embodiment uses a data acquisition controller that intelligently determines whether the photovoltaic-storage system meets the automatic black-start conditions based on photovoltaic power prediction and load prediction power sent by cloud-based AI. Within seconds to minutes after sunlight restoration, the data acquisition controller automatically triggers the black-start process, significantly reducing the power outage time of the photovoltaic-storage system. Simultaneously, this method effectively prevents the photovoltaic-storage system from shutting down again due to insufficient photovoltaic energy after startup, preventing invalid startup. The technical solution in this embodiment does not rely on the photovoltaic inverter's own sunlight prediction power capability, making it a key technology for achieving intelligent black-start and stable operation of the photovoltaic-storage system.

[0087] As one or more specific application embodiments of the present invention, combined with Figure 4 The black-start method for photovoltaic-storage microgrids provided by this invention will be further described in detail, such as... Figure 4 As shown, the specific process is as follows: 1. Settings before automatic black boot: (1) Automatic black start parameter configuration provided by the data acquisition controller, including: Automatic black start basic parameters: automatic black start enable switch and automatic black start minimum state of charge (SOC) threshold; Automatic Black Start Advanced Parameters: Automatic Black Start Minimum Power Enable Switch, Automatic Black Start Minimum Power Setting Value, Automatic Black Start Minimum Voltage Enable Switch, Automatic Black Start Minimum Voltage Setting Value.

[0088] (2) The cloud AI sends the photovoltaic power prediction and load prediction to the data acquisition controller through the MQTT protocol. The data acquisition controller receives the prediction data and saves it locally.

[0089] (3) When the microgrid is in off-grid operation, the lack of sunlight causes the photovoltaic system to be unable to generate electricity, and the energy storage system discharges to supply power to the load. When the real-time charge state of the energy storage system drops below the off-grid discharge cutoff charge state, the data acquisition controller controls the photovoltaic-storage system to shut down and waits for the sunlight to recover before restoring power supply through the black start function.

[0090] 2. Automatic black start action: (1) Data acquisition controller periodically judges automatic black start enable switch Enable auto_blackstart Is it enabled? If not enabled, wait for the user to perform a manual black boot operation. If enabled, proceed to the next step.

[0091] (2) The data acquisition controller determines the real-time state of charge of energy storage in the microgrid. Soc current Is it greater than the minimum state of charge threshold for automatic black start? Soc blackstart_min If the conditions are not met, the automatic black boot process will not be triggered; if the conditions are met, proceed to the next step.

[0092] (3) The data acquisition controller matches the dataset of photovoltaic power prediction and load prediction for the future time period predicted by the cloud AI based on the current time. The time span of this dataset is 2 minutes forward from the current time, in order to avoid the photovoltaic and energy storage system from shutting down again due to insufficient photovoltaic power in a short period of time after startup. If no AI prediction dataset is matched, the automatic black start process will not be triggered; if the match is successful, proceed to the next step.

[0093] (4) If the automatic black start minimum voltage enable switch is enabled Enable auto_blackstart_min_voltage It is now enabled. The data acquisition controller is traversing each photovoltaic inverter in the microgrid and calculating the DC voltage of each photovoltaic inverter. Voltage pv_dc_i and automatic black start minimum voltage Voltage blackstart_min The difference is recorded for grid-connected photovoltaic inverters that meet the minimum voltage requirement for automatic black start and those that do not, before proceeding to the next step. It should be noted that the automatic black start enable switch... Enable auto_blackstart It is the enable switch for the entire automatic black start function; the minimum voltage enable switch for automatic black start. Enable auto_blackstart_min_voltageIt is one of the components used to identify whether the automatic black start conditions are met and whether the machine can start after the automatic black start enable switch is enabled.

[0094] (5) Sum the rated power of all photovoltaic inverters to obtain the total rated power of photovoltaic inverters. P pv_rated_total The total rated power of grid-connected photovoltaic inverters that meet the minimum voltage requirements for automatic black start is the total rated power of photovoltaic inverters with normal voltage. P pv_rated_total_normal_voltage Refresh the calculation dataset to calculate the predicted power of photovoltaic power for each time span. P pv_pre_i_new The photovoltaic power forecast for each time point within the future time period will be updated according to the following formula: The updated photovoltaic (PV) predicted power = PV predicted power at a certain point in time × (total rated power of PV inverters meeting the minimum voltage condition / total rated power of all PV inverters), that is: P pv_pre_i_new =P pv_pre_i × (P pv_rated_total_normal_voltage / P pv_rated_total ) .

[0095] (6) The data acquisition controller calculates the photovoltaic power prediction at each time point in the time span of the dataset. P pv_pre_i_new and load prediction power P load_pre_i If the difference is less than 0, it indicates that the photovoltaic predicted power cannot continuously cover the load predicted power, and the automatic black start process will not be triggered; if the difference is not less than 0 at all time points, proceed to the next step.

[0096] (7) If the automatic black start minimum power enable switch is not turned on, proceed to step (9); otherwise proceed to the next step.

[0097] (8) The data acquisition controller calculates the photovoltaic predicted power after updating at each time point within the time span of the dataset. P pv_pre_i_new With automatic black start minimum power P black_start_min The difference is calculated. If there is a difference less than 0, it indicates that the photovoltaic predicted power cannot continuously cover the minimum power for automatic black start, and the automatic black start process will not be triggered; if the difference at all time points is not less than 0, proceed to the next step.

[0098] (9) If all the conditions in steps (2) to (8) above are met, then the next step can be performed.

[0099] (10) The data acquisition controller sends an off-grid black start setting command to the energy storage converter.

[0100] (11) The energy storage converter host determines whether the state of charge of the corresponding battery meets the black start requirements (based on the state of charge data of the corresponding battery of the energy storage converter, the state of charge must be greater than or equal to 5%). If it meets the requirements, the energy storage converter host performs a black start; if it does not meet the requirements, a black start cannot be performed.

[0101] (12) The data acquisition controller periodically queries the operating status of the energy storage converter host to determine whether the energy storage converter host has been successfully running. If the energy storage converter host is running, it sends a batch start-up command to the photovoltaic inverters that meet the minimum voltage conditions for automatic black start, and the automatic black start is successful.

[0102] (13) For photovoltaic inverters that do not meet the minimum voltage conditions for automatic black start, the data acquisition controller issues start-up commands one by one to avoid impacting the microgrid system by starting all at once.

[0103] (14) If the energy storage converter is not detected to be running successfully within the 5-minute timeout period, the automatic black start is deemed to have failed.

[0104] The black-start method for photovoltaic-storage microgrids provided in this embodiment is applied to industrial, commercial, and islanded microgrids. It enables rapid power restoration after a complete power loss in the off-grid operation state of the microgrid, thereby improving the safety, resilience, and reliability of the microgrid.

[0105] This embodiment also provides a black-start device for a photovoltaic-storage microgrid, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0106] This embodiment provides a black-start device for a photovoltaic-storage microgrid, which includes a photovoltaic-storage system, an energy storage converter, and a photovoltaic inverter, such as... Figure 5 As shown, it includes: The predicted power acquisition module 501 is used to acquire the photovoltaic predicted power and load predicted power issued by cloud AI.

[0107] The automatic black start condition judgment module 502 is used to determine whether the automatic black start condition is met based on the photovoltaic predicted power and the load predicted power.

[0108] The automatic black start execution module 503 is used to control the energy storage converter to perform automatic black start when the automatic black start conditions are met.

[0109] The photovoltaic inverter start-up control module 504 is used to control the photovoltaic inverter to start after detecting that the energy storage converter has successfully performed an automatic black start, so as to restore the power supply of the photovoltaic-energy storage system.

[0110] In some optional implementations, the acquisition of the photovoltaic power forecast and load forecast power issued by cloud AI is performed after the microgrid is off-grid and the energy storage state of charge is lower than the off-grid discharge cutoff charge, causing the photovoltaic and energy storage system to shut down.

[0111] In some optional implementations, the automatic black start condition determination module 502 includes: The enable judgment unit is used to determine whether the automatic black boot enable is enabled. If it is not enabled, it waits for manual black boot.

[0112] The energy storage state of charge determination unit is used to determine whether the current energy storage state of charge is greater than the preset minimum state of charge threshold.

[0113] The photovoltaic power prediction unit is refreshed. If the minimum voltage enable is turned on, it collects the DC voltage of each photovoltaic inverter, calculates the proportion of the total rated power of photovoltaic inverters that meet the minimum voltage condition to the total rated power of all photovoltaic inverters, and uses the proportion to refresh the photovoltaic power prediction at each time point in the future time period.

[0114] The photovoltaic power and load power comparison and judgment unit is used to determine whether the refreshed photovoltaic predicted power is greater than or equal to the load predicted power at each time point in the future time period.

[0115] The photovoltaic power and minimum power comparison and judgment unit is used to determine whether the refreshed photovoltaic predicted power is greater than or equal to the preset minimum power threshold at each time point in the future time period if the minimum power enable is turned on.

[0116] The duration condition judgment unit is used to trigger the automatic black start process when all the above conditions are met and the preset duration is satisfied.

[0117] In an optional implementation, the automatic black start condition determination module 502 further includes: The AI ​​prediction data matching and judgment unit is used to prevent the automatic black start process from being triggered if the predicted photovoltaic power and load power for the future time period predicted by the cloud AI are not matched.

[0118] In one optional implementation, the formula for calculating the refreshed photovoltaic power prediction is: The updated photovoltaic power forecast = photovoltaic power forecast at a certain time point × (total rated power of photovoltaic inverters that meet the minimum voltage condition / total rated power of all photovoltaic inverters).

[0119] In one optional implementation, the automatic black-start execution module 503 includes: The black start execution unit is used to send an automatic black start command to the energy storage converter; obtain the state of charge of the battery corresponding to the energy storage converter; if the state of charge is greater than or equal to a preset percentage, control the energy storage converter to perform automatic black start; otherwise, do not perform automatic black start.

[0120] The timeout failure handling unit is used to determine that the automatic black start has failed if the energy storage converter is not detected to have successfully performed automatic black start within the preset timeout period.

[0121] In one optional implementation, the photovoltaic inverter start-up control module 504 includes: The photovoltaic inverter tiered start-up unit is used to first start up photovoltaic inverters that meet the minimum voltage condition in batches, and then start up photovoltaic inverters that do not meet the minimum voltage condition one by one; meeting the minimum voltage condition means that the DC voltage of the photovoltaic inverter is greater than or equal to the preset automatic black start minimum voltage.

[0122] The black-start device for a photovoltaic-storage microgrid provided in this embodiment of the invention can execute the black-start method for a photovoltaic-storage microgrid provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects for executing the method. Further functional descriptions of the various modules and units described above are the same as in the corresponding embodiments described above, and will not be repeated here.

[0123] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0124] The following is a detailed reference. Figure 6 This diagram illustrates a suitable structural design for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 601, which can perform various appropriate actions and processes based on a program stored in read-only memory (ROM) 602 or a program loaded from memory 608 into random access memory (RAM) 603. RAM 603 also stores various programs and data required for the operation of the electronic device. The processor 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0125] Typically, the following devices can be connected to I / O interface 605: input devices 606 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 607 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 608 including, for example, magnetic tapes, hard disks, etc.; and communication devices 609. Communication device 609 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 6 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0126] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 609, or installed from a memory 608, or installed from a ROM 602. When the computer program is executed by the processor 601, it performs the functions defined in the black-start method for a photovoltaic-storage microgrid according to embodiments of the present invention.

[0127] Figure 6 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of the present invention.

[0128] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that the computer, processor, microprocessor controller, or programmable hardware includes storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the black-start method of the photovoltaic-storage microgrid shown in the above embodiments is implemented.

[0129] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0130] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A black-start method for a photovoltaic-storage microgrid, characterized in that, The photovoltaic-storage microgrid includes a photovoltaic-storage system, an energy storage converter, and a photovoltaic inverter; the method includes: The photovoltaic power forecast and load forecast power are obtained from the cloud AI. The acquisition of the photovoltaic power forecast and load forecast power is performed after the microgrid is off-grid and the energy storage state of charge is lower than the off-grid discharge cutoff charge, causing the photovoltaic and energy storage system to be shut down. Based on the photovoltaic predicted power and load predicted power, determine whether the automatic black start conditions are met, including: Determine if automatic black boot is enabled; if not, wait for manual black boot. Determine whether the current state of charge of the energy storage is greater than the preset minimum state of charge threshold; If the minimum voltage enable is turned on, the DC voltage of each photovoltaic inverter is collected, the proportion of the total rated power of the photovoltaic inverters that meet the minimum voltage condition to the total rated power of all photovoltaic inverters is calculated, and the photovoltaic predicted power at each time point in the future time period is updated using the proportion. Determine whether the updated photovoltaic power forecast is greater than or equal to the load forecast power at all points in the future time period. If the minimum power enable is turned on, it is determined whether the refreshed photovoltaic predicted power is greater than or equal to the preset minimum power threshold at each time point in the future time period. When all the above conditions are met and the preset duration is satisfied, the automatic black start process is triggered. When the conditions for automatic black start are met, the energy storage converter is controlled to perform automatic black start; After detecting that the energy storage converter has successfully performed an automatic black start, the photovoltaic inverter is controlled to start in order to restore power supply to the photovoltaic-energy storage system.

2. The method according to claim 1, characterized in that, The determination of whether the automatic black start condition is met also includes: If the predicted photovoltaic power and load power for the future time period are not matched by cloud AI, the automatic black start process will not be triggered.

3. The method according to claim 1, characterized in that, The formula for calculating the updated photovoltaic power prediction is as follows: The updated photovoltaic power forecast = photovoltaic power forecast at a certain time point × (total rated power of photovoltaic inverters that meet the minimum voltage condition / total rated power of all photovoltaic inverters).

4. The method according to claim 1, characterized in that, The control of the energy storage converter to perform automatic black start includes: Send an automatic black start command to the energy storage converter; The state of charge (SOC) of the battery corresponding to the energy storage converter is obtained. If the SOC is greater than or equal to a preset percentage, the energy storage converter is controlled to perform an automatic black start; otherwise, the automatic black start is not performed.

5. The method according to claim 4, characterized in that, The method for controlling the energy storage converter to perform automatic black start also includes: If the energy storage converter is not detected to have successfully performed an automatic black start within the preset timeout period, the automatic black start is deemed to have failed.

6. The method according to claim 1, characterized in that, After detecting that the energy storage converter has successfully performed an automatic black start, the photovoltaic inverter is controlled to start, including: First, start up photovoltaic inverters that meet the minimum voltage condition in batches, and then start up photovoltaic inverters that do not meet the minimum voltage condition one by one; the minimum voltage condition means that the DC voltage of the photovoltaic inverter is greater than or equal to the preset automatic black start minimum voltage.

7. A black-start device for a photovoltaic-storage microgrid, characterized in that, The black-start method for a photovoltaic-storage microgrid according to any one of claims 1 to 6, wherein the photovoltaic-storage microgrid includes a photovoltaic-storage system, an energy storage converter, and a photovoltaic inverter, and the device includes: The predicted power acquisition module is used to acquire the photovoltaic predicted power and load predicted power issued by cloud AI. The automatic black start condition judgment module is used to determine whether the automatic black start condition is met based on the photovoltaic predicted power and the load predicted power. The automatic black start execution module is used to control the energy storage converter to perform automatic black start when the automatic black start conditions are met. The photovoltaic inverter start-up control module is used to control the photovoltaic inverter to start after detecting that the energy storage converter has successfully performed an automatic black start, so as to restore the power supply of the photovoltaic-energy storage system.

8. An electronic device, characterized in that, include: The system includes a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes the computer instructions to perform the black-start method of the photovoltaic-storage microgrid as described in any one of claims 1 to 6.

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