Power supply control method, device, equipment, medium and program product of charging station

Abstract

This application relates to a power supply control method, apparatus, computer equipment, computer-readable storage medium, and computer program product for a charging station. The method includes: when the target charging station's power supply mode is grid-connected, acquiring multi-energy coordination data of the target charging station, including grid-side data, resource-side data, and load-side data; if, based on the grid-side data, it is determined that the power supply mode switching conditions are met, switching the power supply mode to off-grid mode; and based on the resource-side data and load-side data, determining the power allocation strategy matched to the target charging station in off-grid mode; and controlling the power supply of the target charging station according to the power allocation strategy, thereby improving the reliability of power supply control.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a power supply control method, apparatus, computer equipment, computer-readable storage medium, and computer program product for a charging station. Background Technology

[0002] With the development of computer technology, its application in the field of energy management and control is becoming increasingly widespread and in-depth. As the demand for ultra-high-power charging of electric passenger vehicles surges, megawatt-level charging stations generally integrate multiple energy sources such as photovoltaics and energy storage, which puts forward higher requirements for the power supply control of charging stations.

[0003] In related technologies, grid-connected and off-grid control is performed based on the interaction between the power grid and charging piles. Subsequently, a power allocation strategy based on average power distribution is used for power supply control in off-grid mode. However, the uniform use of the same power allocation strategy in these technologies can easily lead to unreliable emergency power supply needs, resulting in low reliability of power supply control. Summary of the Invention

[0004] Therefore, it is necessary to provide a power supply control method, device, computer equipment, computer-readable storage medium, and computer program product for charging stations that can improve the reliability of power supply control, in order to address the above-mentioned technical problems.

[0005] In a first aspect, this application provides a power supply control method for a charging station, comprising:

[0006] When the power supply mode of the target charging station is grid-connected, acquire the multi-energy coordination data of the target charging station, which includes grid-side data, resource-side data and load-side data;

[0007] If the power supply mode switching conditions are met based on the grid-side data, the power supply mode is switched to off-grid mode, and the power allocation strategy matched to the target charging station in the off-grid mode is determined based on the resource-side data and the load-side data.

[0008] The power supply to the target charging station is controlled according to the power allocation strategy.

[0009] Secondly, this application also provides a power supply control device for a charging station, comprising:

[0010] The data acquisition module is used to acquire multi-energy collaborative data of the target charging station when the power supply mode of the target charging station is grid-connected. The multi-energy collaborative data includes grid-side data, resource-side data and load-side data.

[0011] The strategy determination module is used to switch the power supply mode to off-grid mode when the power supply mode switching conditions are met based on the grid-side data, and to determine the power allocation strategy matched to the target charging station in the off-grid mode based on the resource-side data and the load-side data.

[0012] The power supply control module is used to control the power supply of the target charging station according to the power allocation strategy.

[0013] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0014] When the power supply mode of the target charging station is grid-connected, acquire the multi-energy coordination data of the target charging station, which includes grid-side data, resource-side data and load-side data;

[0015] If the power supply mode switching conditions are met based on the grid-side data, the power supply mode is switched to off-grid mode, and the power allocation strategy matched to the target charging station in the off-grid mode is determined based on the resource-side data and the load-side data.

[0016] The power supply to the target charging station is controlled according to the power allocation strategy.

[0017] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0018] When the power supply mode of the target charging station is grid-connected, acquire the multi-energy coordination data of the target charging station, which includes grid-side data, resource-side data and load-side data;

[0019] If the power supply mode switching conditions are met based on the grid-side data, the power supply mode is switched to off-grid mode, and the power allocation strategy matched to the target charging station in the off-grid mode is determined based on the resource-side data and the load-side data.

[0020] The power supply to the target charging station is controlled according to the power allocation strategy.

[0021] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0022] When the power supply mode of the target charging station is grid-connected, acquire the multi-energy coordination data of the target charging station, which includes grid-side data, resource-side data and load-side data;

[0023] If the power supply mode switching conditions are met based on the grid-side data, the power supply mode is switched to off-grid mode, and the power allocation strategy matched to the target charging station in the off-grid mode is determined based on the resource-side data and the load-side data.

[0024] The power supply to the target charging station is controlled according to the power allocation strategy.

[0025] The aforementioned power supply control method, device, computer equipment, computer-readable storage medium, and computer program product for charging stations acquire multi-energy coordination data of the target charging station in real time when the target charging station's power supply mode is grid-connected. Since this multi-energy coordination data includes grid-side data, resource-side data, and load-side data, the power supply mode is promptly switched to off-grid mode when the grid-side data determines that the power supply mode switching conditions are met, achieving seamless grid-connected / off-grid switching. Then, based on resource-side and load-side data, a more suitable power allocation strategy for the target charging station in off-grid mode can be flexibly and accurately determined from both resource and load perspectives. Thus, by controlling the power supply of the target charging station according to the power allocation strategy, the low-quality power supply control achieved by using a fixed power allocation strategy is avoided, improving the reliability of power supply control for the target charging station. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is an application environment diagram of the power supply control method for a charging station in one embodiment;

[0028] Figure 2 This is a flowchart illustrating the power supply control method for a charging station in one embodiment;

[0029] Figure 3 This is an architectural diagram of a target charging station in one embodiment;

[0030] Figure 4 This is a schematic diagram illustrating the detailed power supply control process of a charging station in one embodiment;

[0031] Figure 5 This is a structural block diagram of the power supply control device for a charging station in one embodiment;

[0032] Figure 6 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0034] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0035] The power supply control method for charging stations provided in this application embodiment can be applied to, for example... Figure 1 The application environment shown is as follows. The target charging station 100 includes a charging pile 101, an energy storage device 102, a photovoltaic device 103, and a charging station control device 104. The charging pile 101, the energy storage device 102, and the photovoltaic device 103 communicate with the charging station control device 104.

[0036] In some embodiments, when the power supply mode of the target charging station 100 is grid-connected, the charging station control device 104 acquires multi-energy coordination data of the target charging station, including grid-side data, resource-side data, and load-side data. When the charging station control device 104 determines, based on the grid-side data, that the power supply mode switching conditions are met, the charging station control device 104 switches the power supply mode to off-grid mode and determines the power allocation strategy matched to the target charging station in off-grid mode based on the resource-side data and load-side data. The charging station control device 104 controls the power supply of the target charging station according to the power allocation strategy to adaptively allocate power to the charging piles 101, energy storage devices 102, and photovoltaic devices 103 in the target charging station 100.

[0037] The energy storage device 102 has an energy storage function. Furthermore, the energy storage device 102 is equipped with an energy storage system, meaning the energy storage system also has an energy storage function. The photovoltaic device 103 converts acquired solar energy into electrical energy and also has an energy storage function. Furthermore, the photovoltaic device 103 is equipped with a photovoltaic system, which also converts acquired solar energy into electrical energy and has an energy storage function. The charging station control device 104 controls the power supply to the target charging station 100. The charging station control device 104 is equipped with a charging station controller, which controls the power supply to the target charging station 100. The charging station control device can be a server, which can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0038] In one exemplary embodiment, such as Figure 2 As shown, a power supply control method for a charging station is provided, which is applied to... Figure 1 Taking the charging station control device 104 as an example, the explanation includes the following steps S202 to S206. Wherein:

[0039] Step S202: When the power supply mode of the target charging station is grid-connected, acquire the multi-energy coordination data of the target charging station. The multi-energy coordination data includes grid-side data, resource-side data and load-side data.

[0040] The target charging station is the charging station to be controlled for power supply. A charging station is a dedicated site or location that centrally configures charging equipment and related supporting facilities to provide power replenishment services for electric vehicles (such as electric cars and electric buses). In some embodiments, the target charging station can be a public urban charging station, a highway service area charging station, or a logistics park integrated photovoltaic-storage-charging station, etc. Grid-connected mode is a power supply mode in which the target charging station connects to the power grid to achieve bidirectional interaction of electrical energy (e.g., it can draw power from the grid to charge vehicles, and, under certain conditions, feed excess electricity from renewable energy generation or energy storage systems within the target charging station back to the grid). Multi-energy collaborative data refers to data on the collaboration of multiple energy sources. This multi-energy collaborative data includes grid-side data, resource-side data, and load-side data. Grid-side data reflects the relevant energy data of the power grid associated with the target charging station. Optionally, grid-side data includes the index values ​​of different grid indicators, which can be grid voltage indicators, grid frequency indicators, grid phase indicators, and distribution feeder current indicators. Resource-side data reflects the energy data of energy storage and photovoltaic equipment in the target charging station. This data includes the values ​​of various resource indicators, such as photovoltaic array output power, photovoltaic output capacity, irradiance (predicting short-term photovoltaic output), energy storage SOC (State of Charge), and energy storage charging / discharging current / voltage. Load-side data reflects the relevant energy data of the charging piles. This data includes the values ​​of various load indicators, such as the real-time power of each charging pile, the load of each charging pile, the type of charging demand (emergency / residential / backup), and the electric vehicle battery status (SOC, charging rate demand).

[0041] Optionally, if the target charging station's current power supply mode is grid-connected, the charging station control equipment acquires data from data collection at the target charging station. This data includes grid-based data, resource-based data, and load-side data. The charging station control equipment performs data preprocessing (e.g., data cleaning, spatiotemporal alignment) on the acquired data to obtain processed acquired data, which is then used as multi-dimensional collaborative data. For example, the charging station control equipment performs data preprocessing on the grid-based data, resource-based data, and load-side data respectively to obtain grid-side data, resource-side data, and load-side data. Based on these data, multi-energy collaborative data is determined. Of course, in some embodiments, the charging station control equipment can also communicate with edge computing nodes. The charging station control equipment sends the collected data to the edge computing nodes, so that the edge computing nodes can preprocess the grid-collected data, resource-collected data, and load-side data respectively to obtain grid-side data, resource-side data, and load-side data. Based on the grid-side data, resource-side data, and load-side data, multi-energy coordinated data is determined, and the edge computing nodes send the multi-energy coordinated data to the charging station control equipment. In this way, the charging station control equipment avoids directly preprocessing the large amount of collected data, effectively reducing the computing cost of the charging station control equipment.

[0042] Step S204: If the power supply mode switching conditions are met based on grid-side data, switch the power supply mode to off-grid mode, and determine the power allocation strategy matched to the target charging station in off-grid mode based on resource-side data and load-side data.

[0043] The power supply mode switching condition refers to the conditions for switching from grid-connected mode to off-grid mode. Off-grid mode is a power supply mode in which the target charging station operates completely independently of the power grid, relying solely on its own power generation equipment (such as photovoltaic equipment) or energy storage equipment to provide power to vehicles. The power allocation strategy is the strategy that instructs the photovoltaic equipment and energy storage equipment in the target charging station to allocate power to the charging piles respectively.

[0044] Optionally, the charging station control equipment determines whether the power supply mode switching conditions are met based on grid-side data. If the conditions are met, the charging station control equipment switches the power supply mode from grid-connected mode to off-grid mode. Based on resource-side and load-side data, the charging station control equipment selects the power allocation strategy that matches the target charging station in the off-grid mode from multiple preset power allocation strategies.

[0045] For example, the charging station control equipment obtains the index values ​​of various power grid indicators from the power grid side data. For each power grid indicator, it determines the corresponding switching score, and merges the switching scores of various power grid indicators to obtain the target switching score. If the target switching score is greater than or equal to the score threshold, it is determined that the power supply mode switching condition is met.

[0046] For example, the charging station control equipment generates a strategy selection prompt text based on the index values ​​of various resource indicators in the resource-side data, the index values ​​of various load indicators in the load-side data, and multiple preset power allocation strategies. A large language model is invoked to perform semantic understanding on the strategy selection prompt text, in order to filter out the power allocation strategy matching the target charging station in the off-grid mode from the multiple preset power allocation strategies.

[0047] In some embodiments, the method further includes: obtaining the current grid voltage value and the current frequency from grid-side data; determining the voltage drop magnitude based on the current grid voltage value; determining that the power supply mode switching condition is met when the voltage drop magnitude drops to an amplitude threshold and the current frequency exceeds a preset frequency threshold; and determining that the power supply mode switching condition is not met when the voltage drop magnitude does not drop to an amplitude threshold or when the current frequency is less than or equal to a preset frequency threshold.

[0048] In some embodiments, the amplitude threshold can be 10%, and the preset frequency threshold is 0.5Hz.

[0049] For example, the charging station control equipment obtains the current grid pressure value (voltage indicator) and the current frequency (frequency indicator) from the grid-side data. The charging station control equipment acquires the historical grid-side dataset for the target charging station, retrieves the historical grid-side data corresponding to each historical moment from the historical grid-side dataset, and filters out the historical moment with the smallest time difference from the current moment, designating this filtered historical moment as the closest historical moment to the current moment. Based on the historical grid-side data of the closest historical moment, the charging station control equipment obtains the historical grid pressure value, calculates the difference between the historical grid pressure value and the current grid pressure value, and obtains the voltage drop magnitude based on the ratio of this difference to the historical grid pressure value.

[0050] For example, the charging station control equipment verifies whether the voltage drop has dropped to an amplitude threshold, that is, whether the voltage drop is greater than or equal to the amplitude threshold; and verifies whether the current frequency exceeds a frequency threshold; if the voltage drop has dropped to the amplitude threshold and the current frequency exceeds a preset frequency threshold, it determines that the power supply mode switching condition is met; if the voltage drop has not dropped to the amplitude threshold, or if the current frequency is less than or equal to the preset frequency threshold, it determines that the power supply mode switching condition is not met.

[0051] In the above embodiments, after obtaining the current voltage value and current frequency from the grid side data, the voltage drop magnitude can be queried in a timely manner. Based on the comparison between the voltage drop magnitude and the magnitude threshold, as well as the comparison between the current frequency and the preset frequency threshold, it can be accurately determined whether the power supply mode switching conditions are met, so as to achieve a rapid response to the operation mode switching.

[0052] In some embodiments, when the conditions for switching the power supply mode are met, the charging station control equipment, combining short-term photovoltaic output prediction (based on irradiance data) and energy storage SOC, issues an off-grid command within a short period, disconnects the main grid connection switch, and simultaneously activates the islanding operation control strategies of the photovoltaic equipment, energy storage equipment, and charging piles (the photovoltaic inverter switches to islanding mode, the energy storage starts up to ensure power supply, and the charging pile charges at the lowest power or suspends charging power), to achieve the switch of the power supply mode to off-grid mode. During the switching process, the load power and power generation are reduced to the minimum (e.g., the photovoltaic inverter stops outputting or outputs at minimum power, the energy storage stops outputting or outputs at minimum power, and the charging pile charges at the lowest power or suspends charging power). A master controller is established using one energy storage inverter with the grid frequency as the off-grid frequency, and other inverters act as followers of the master controller, while ensuring that the power output of the photovoltaic energy storage is equal to the load power of the charging equipment (based on energy storage discharge).

[0053] In some embodiments, determining the power allocation strategy matched to the target charging station in off-grid mode based on resource-side data and load-side data includes: obtaining the current photovoltaic output of the target charging station from the resource-side data, and determining the load of charging piles of different priorities in the target charging station from the load-side data; determining the matched photovoltaic output scenario based on the current photovoltaic output and the load of charging piles of different priorities; and selecting the power allocation strategy corresponding to the photovoltaic output scenario from multiple power allocation strategies based on the matched photovoltaic output scenario, wherein the selected power allocation strategy is the power allocation strategy matched to the target charging station in off-grid mode.

[0054] Among them, the photovoltaic output scenario reflects the output scenario of photovoltaic equipment. The current photovoltaic output refers to the photovoltaic output of the photovoltaic equipment at the current moment, which is the power output of the photovoltaic equipment. The charging pile load refers to the power demand of the charging pile during operation, that is, the power required by the charging pile.

[0055] Priority is used to reflect the urgency of the charging demand for a given charging station. For example, a higher priority indicates a higher urgency of the charging demand. In some embodiments, charging stations include dedicated charging stations for emergency vehicles, essential public charging stations, and commercial backup charging stations, etc. Specifically, dedicated charging stations for emergency vehicles have a higher priority than essential public charging stations, which in turn have a higher priority than commercial backup charging stations.

[0056] Optionally, after determining to switch the power supply mode to off-grid mode, the charging station control equipment obtains the current photovoltaic output of the target charging station from the resource-side data and determines the load of charging piles with different priorities in the target charging station from the load-side data.

[0057] Optionally, the charging station control equipment, based on the current photovoltaic output and the load of charging piles with different priorities, invokes a scene recognition model to determine the photovoltaic output scene matched to the target charging station. This scene recognition model is used to identify patterns in photovoltaic output scenes; in some embodiments, the scene recognition model is implemented based on a large language model.

[0058] Optionally, the charging station control equipment, based on comparisons of the current photovoltaic output with charging piles of different priorities, selects the photovoltaic output scenario matching the target charging station from multiple preset photovoltaic output scenarios. For example, if the photovoltaic output is greater than the load of all charging piles, and the maximum load is determined from the loads of the charging piles, and the difference between the photovoltaic output and the maximum load is greater than a first difference, then the matched photovoltaic output scenario is determined to be a high photovoltaic output scenario. If the difference between the photovoltaic output and the maximum load is greater than a second difference but less than the first difference, then the matched photovoltaic output scenario is determined to be a medium photovoltaic output scenario. If the difference between the photovoltaic output and the maximum load is less than the second difference, then the matched photovoltaic output scenario is determined to be a low photovoltaic output scenario. The first difference is greater than the second difference.

[0059] It should be noted that high photovoltaic output scenarios refer to scenarios with high photovoltaic output; medium photovoltaic output scenarios refer to scenarios with relatively high photovoltaic output; and low photovoltaic output scenarios refer to scenarios with low photovoltaic output. It can be understood that the photovoltaic output of high photovoltaic output scenarios is greater than that of medium photovoltaic output scenarios, and the photovoltaic output of medium photovoltaic output scenarios is greater than that of low photovoltaic output scenarios.

[0060] In some embodiments, the correspondence between photovoltaic output scenarios and power allocation strategies is obtained, and based on the correspondence and the matched photovoltaic output scenarios, a power allocation strategy corresponding to the photovoltaic output scenarios is selected from multiple power allocation strategies.

[0061] In the above embodiments, based on the current photovoltaic output and the load of charging piles with different priorities, the current photovoltaic output scenario of the target charging station can be comprehensively identified from both resource and load dimensions, thereby enabling the accurate selection of a suitable power allocation strategy.

[0062] In some embodiments, determining a matching photovoltaic output scenario based on the current photovoltaic output and the loads of charging piles with different priorities includes: superimposing the loads of charging piles with first priority and charging piles with second priority to obtain a load sum value, where the first priority is higher than the second priority; determining the matching photovoltaic output scenario as a high photovoltaic output scenario when the current photovoltaic output is greater than or equal to the load sum value; determining the matching photovoltaic output scenario as a medium photovoltaic output scenario when the current photovoltaic output is greater than or equal to the load of the charging pile with first priority and the current photovoltaic output is less than the load sum value; and determining the matching photovoltaic output scenario as a low photovoltaic output scenario when the current photovoltaic output is less than the load of the charging pile with first priority.

[0063] There are multiple priorities, and each priority level has at least one corresponding charging pile. For example, the target charging station has three priorities, which are sorted from high to low as first priority, second priority, and third priority. The charging piles of the first priority can be dedicated charging piles for emergency vehicles; the charging piles of the second priority can be charging piles for essential public services; and the charging piles of the third priority can be commercial backup charging piles.

[0064] In some embodiments, the power allocation strategy for high photovoltaic output scenarios prioritizes power supply from photovoltaic devices to meet the power demands of first-priority and second-priority charging piles, while third-priority charging piles are supplied with limited low-power power, and the remaining photovoltaic power is used to charge energy storage devices (to avoid photovoltaic power curtailment). In medium photovoltaic output scenarios, the power allocation strategy involves photovoltaic devices supplying power solely to first-priority charging piles, energy storage devices supplementing the full-power demand of second-priority charging piles, and third-priority charging piles receiving no power. In low photovoltaic output scenarios, the power allocation strategy involves photovoltaic devices and energy storage devices working together to supply power to first-priority charging piles, and triggering protection when the energy storage SOC is low, retaining only the minimum sustaining power of first-priority charging piles (to avoid over-discharge of energy storage), while second-priority and third-priority charging piles receive no power.

[0065] In the above embodiments, when the current photovoltaic output is greater than or equal to the sum of the loads of the first-priority charging piles and the second-priority charging piles, the matching photovoltaic output scenario can be accurately determined as a high photovoltaic output scenario; when the current photovoltaic output is less than the sum of the loads, but the current photovoltaic output is greater than or equal to the load of the first-priority charging piles, the matching photovoltaic output scenario can be accurately determined as a medium photovoltaic output scenario; when the current photovoltaic output is less than the load of the first-priority charging piles, the matching photovoltaic output scenario can be accurately determined as a low photovoltaic output scenario. Thus, the current photovoltaic output scenario of the target charging station can be accurately identified, thereby enabling the accurate selection of a suitable power allocation strategy.

[0066] In some embodiments, the method further includes: before the energy storage device discharges to the minimum charge level, handing over the off-grid frequency main controller of the energy storage device to the photovoltaic inverter (the one with the highest on-site power generation, or a designated one).

[0067] Step S206: Control the power supply to the target charging station according to the power allocation strategy.

[0068] Optionally, the charging station control equipment performs corresponding charging control on the charging piles of the target charging station according to the matched power allocation strategy. For example, if the matched power allocation strategy is the power allocation strategy corresponding to a high photovoltaic output scenario, the charging station control equipment prioritizes the use of photovoltaic equipment for power supply to meet the power requirements of the first-priority charging piles and the second-priority charging piles, while the third-priority charging piles are supplied with limited low power, and the remaining photovoltaic power is used to charge the energy storage equipment (to avoid photovoltaic power curtailment).

[0069] For example, if the matching power allocation strategy is the power allocation strategy corresponding to the medium photovoltaic output scenario, then the photovoltaic equipment supplies power to the first priority charging piles alone, the energy storage equipment supplements the full power demand of the second priority charging piles, and the third priority charging piles suspend power supply.

[0070] For example, if a matching power allocation strategy is used, the power allocation strategy corresponding to the low photovoltaic output scenario is that the photovoltaic equipment and energy storage equipment work together to supply the first priority charging pile, and when the energy storage SOC is low, the protection is triggered to retain only the minimum maintenance power of the first priority charging pile (to avoid over-discharge of energy storage), while the second priority charging pile and the third priority charging pile are suspended from power supply.

[0071] In the aforementioned power supply control method for charging stations, when the target charging station's power supply mode is grid-connected, multi-energy coordination data of the target charging station is acquired in real time. Since this multi-energy coordination data includes grid-side data, resource-side data, and load-side data, the power supply mode is promptly switched to off-grid mode when the grid-side data determines that the power supply mode switching conditions are met, achieving seamless grid-connected / off-grid switching. Then, based on resource-side and load-side data, a more suitable power allocation strategy for the target charging station in off-grid mode can be flexibly and accurately determined from both resource and load perspectives. Thus, by adjusting the power allocation strategy, the power supply to the target charging station can be adaptively controlled, avoiding low-quality power supply control using a fixed power allocation strategy and improving the reliability of power supply control for the target charging station.

[0072] In some embodiments, after controlling the power supply to the target charging station according to the power allocation strategy, the method further includes: acquiring new grid-side data; verifying the duration of the grid stability conditions if the new grid-side data is found to meet the grid stability conditions; and switching the off-grid mode back to the grid-connected mode if the duration is greater than or equal to a duration threshold.

[0073] Among them, the grid stability condition refers to the grid to which the target charging station is connected is stable. It should be noted that meeting the grid stability condition means that it is permissible to switch from off-grid mode to grid-connected mode.

[0074] In some embodiments, the charging station control equipment acquires new grid-side data within a preset time period. Based on this data, it determines the voltage and frequency at each moment within the preset time period. Based on the voltage values ​​at each moment, it determines the voltage variation amplitude; and based on the frequency at each moment, it determines the frequency variation amplitude. If the voltage variation amplitude is less than a first amplitude threshold and the frequency variation amplitude is less than a second amplitude threshold, it indicates that the grid voltage and frequency are stable, and the grid stability condition is met. The preset time period refers to the period from the start time of the power allocation strategy execution to the target time; the duration between the target time and the start time is the preset duration. The preset duration can be a pre-defined duration or determined based on the attribute information of the target charging station.

[0075] In some embodiments, after determining that the grid stability conditions are met, the duration for which the grid stability conditions are met is determined, where the duration refers to the length of time the grid stability conditions are maintained. If the duration is greater than or equal to a duration threshold, the off-grid mode is switched back to the grid-connected mode.

[0076] In the above embodiments, by verifying whether the new grid-side data meets the grid stability conditions, the timing for switching back to grid-connected mode can be determined flexibly and promptly, further improving the reliability of power supply control.

[0077] In some embodiments, the method further includes: reducing the energy storage power of the target charging station; and after restoring power supply to each charging pile in the target charging station when the power is reduced to a power threshold, adjusting the photovoltaic grid-connected power at a preset rate.

[0078] In some embodiments, when the duration is greater than or equal to a duration threshold, combined with stable photovoltaic output and a state of charge (SOC) of energy storage exceeding a threshold, a grid connection preparation process is triggered. Then, a grid connection recovery phase is executed, which coordinates parameter matching between the photovoltaic equipment, energy storage equipment, and the grid to achieve soft synchronous grid connection: adjusting the output voltage / frequency of the photovoltaic inverter (tracking grid parameters) and the charging / discharging power of the energy storage converter (correcting the phase difference between the site side and the grid side), controlling the deviations within a certain range (voltage deviation less than the threshold, frequency deviation less than the threshold, phase difference less than the threshold), thereby completing the pre-synchronization of parameters. Afterwards, the charging station control equipment lowers the energy storage power of the target charging station; once the power threshold is reached, power supply to each charging pile in the target charging station is restored, and the photovoltaic grid-connected power is adjusted according to a preset rate.

[0079] For example, before grid connection, the charging station control equipment reduces the load power and power generation of the energy storage device to the minimum (the photovoltaic inverter stops outputting, the energy storage stops outputting, or outputs at the minimum power that the charging equipment can output, and the charging pile charges at the minimum power or suspends charging power); first, the energy storage device is restored so that the energy storage device discharges to meet the minimum output power of the charging pile, then the power supply to the charging pile load is restored (first priority charging piles are restored first, second priority charging piles are restored, and then third priority charging piles are restored gradually), and finally the photovoltaic output is gradually adjusted (the photovoltaic grid-connected power is increased at a lower rate).

[0080] For example, the grid-connected current is monitored in real time through edge computing. If the inrush current exceeds the threshold, the output of photovoltaic and energy storage is immediately reduced to ensure that there is no impact during the grid connection process; thereby achieving impact suppression.

[0081] In the above embodiments, the energy storage power of the target charging station is reduced; after the power is reduced to the power threshold, the power supply to each charging pile in the target charging station is restored, and the photovoltaic grid-connected power is adjusted at a preset rate; thereby, distributed grid connection is achieved, ensuring grid stability and grid security.

[0082] In a specific embodiment, such as Figure 3 The diagram shown is an architecture diagram of a target charging station in one embodiment. Figure 3 This diagram illustrates the connection and communication relationships between each unit in the charging station control equipment and the power grid. The charging station control equipment includes a multi-energy collaborative data detection unit, an off-grid / grid switching unit, an islanded mode multi-energy collaborative power allocation unit, a grid-connected recovery multi-energy collaborative soft synchronization unit, and a grid-connected recovery multi-energy collaborative soft synchronization unit. The following section will discuss... Figure 4 Please provide an explanation, such as Figure 4 The diagram shown is a detailed flowchart of the power supply control process for a charging station in one embodiment.

[0083] Step 1: The multi-energy collaborative data detection unit preprocesses the collected data to obtain multi-energy collaborative data, and sends it to the grid-connected switching determination unit to continue executing Step 2.

[0084] Step 2: The multi-energy collaborative data detection unit determines whether off-grid mode has been triggered. If not, it determines that grid-connected mode has been triggered and proceeds to Step 3. If so, it indicates that the current power supply mode is grid-connected mode, and a switching command is sent to switch the off-grid switching unit to off-grid mode. A switching completion command is also sent to the islanded mode multi-energy collaborative power allocation strategy unit. Subsequently, after receiving the switching completion command, the islanded mode multi-energy collaborative power allocation unit triggers off-grid mode within a very short time. The islanded mode multi-energy collaborative power allocation strategy unit combines the real-time output of photovoltaic power, the SOC of energy storage, and the priority of charging piles to calculate the power commands of each device and control the photovoltaic and energy storage to supply power according to the commands, ensuring critical loads.

[0085] Specifically, the multi-energy coordinated data detection unit obtains the current grid voltage and frequency from the grid-side data; based on the current grid voltage, it determines the voltage drop magnitude; if the voltage drop magnitude drops to a threshold value and the current frequency exceeds a preset frequency threshold, it determines that the power supply mode switching conditions are met; if the voltage drop magnitude does not drop to the threshold value, or if the current frequency is less than or equal to the preset frequency threshold, it determines that the power supply mode switching conditions are not met. When the power supply mode switching conditions are determined to be met based on the grid-side data, the multi-energy coordinated data detection unit sends a switching command to switch the off-grid switching unit to off-grid mode.

[0086] Specifically, after receiving the switching completion instruction, the islanded mode multi-energy collaborative power distribution unit obtains the current photovoltaic output of the target charging station from the resource-side data and determines the load of charging piles with different priorities in the target charging station from the load-side data.

[0087] In the islanded mode, the multi-energy collaborative power allocation unit superimposes the loads of the first-priority charging piles and the second-priority charging piles to obtain a load sum value, with the first priority being higher than the second priority. When the current photovoltaic output is greater than or equal to the load sum value, the matched photovoltaic output scenario is determined to be a high photovoltaic output scenario. When the current photovoltaic output is greater than or equal to the load of the first-priority charging pile and the current photovoltaic output is less than the load sum value, the matched photovoltaic output scenario is determined to be a medium photovoltaic output scenario. When the current photovoltaic output is less than the load of the first-priority charging pile, the matched photovoltaic output scenario is determined to be a low photovoltaic output scenario.

[0088] The islanded mode multi-energy collaborative power allocation unit selects the power allocation strategy corresponding to the photovoltaic output scenario from multiple power allocation strategies based on the matching photovoltaic output scenario. The selected power allocation strategy is the power allocation strategy matched to the target charging station in off-grid mode.

[0089] Step 3: Trigger grid connection preparation: When grid connection is restored, the grid connection restoration multi-energy coordinated soft synchronization unit adjusts the photovoltaic inverter, energy storage converter, and charging load to make the deviation between the parameters on the site side and the grid side less than the threshold, thus completing the soft synchronization pre-preparation and continuing to step 4.

[0090] Specifically, the grid-connected recovery multi-energy coordinated soft synchronization unit acquires new grid-side data. If the new grid-side data is found to meet the grid stability conditions, the duration of meeting the grid stability conditions is verified. If the duration is greater than or equal to the duration threshold, the off-grid mode is switched back to grid-connected mode.

[0091] Step 4: Multi-energy coordinated phased grid connection: Operate in the following steps in the order of "energy storage grid connection → charging pile restoration → photovoltaic grid connection", and monitor the inrush current in real time to ensure stable grid connection.

[0092] Specifically, the grid-connected restoration multi-energy coordinated soft synchronization unit lowers the energy storage power of the target charging station; after lowering it to the power threshold, it restores power supply to each charging pile in the target charging station, and then adjusts the photovoltaic grid-connected power at a preset rate to achieve "energy storage grid connection → charging pile restoration → photovoltaic grid connection".

[0093] It should be noted that the above process improves the efficiency of multi-energy resource utilization. Specifically, through the coordinated scheduling of photovoltaic equipment, energy storage equipment, and charging piles, the green electricity absorption rate increases when the grid is normal, the curtailment rate of photovoltaic equipment decreases in islanded mode, and the lifespan of energy storage equipment is extended (avoiding over-discharge). It also achieves seamless switching between grid-connected and off-grid environments, meaning rapid fault response and off-grid switching, uninterrupted charging, and significantly improved user experience and equipment safety. Furthermore, it strengthens emergency power supply guarantees by prioritizing power allocation based on multi-energy coordination, ensuring high power supply guarantees for dedicated emergency vehicle charging piles and public charging piles. It also significantly reduces grid connection impact by using multi-energy coordinated soft synchronization technology to control the grid connection inrush current near the rated current, avoiding secondary grid fluctuations and equipment damage. Finally, it achieves strong adaptability across all scenarios, specifically designed for megawatt-level power plants, compatible with multi-energy access (photovoltaics, energy storage, and charging), adaptable to high-load and high-fluctuation scenarios, and with stability and reliability meeting engineering application requirements.

[0094] In the above embodiments, when the target charging station's power supply mode is grid-connected, multi-energy coordination data of the target charging station is acquired in real time. Since this multi-energy coordination data includes grid-side data, resource-side data, and load-side data, the power supply mode is promptly switched to off-grid mode when the grid-side data determines that the power supply mode switching conditions are met, achieving seamless grid-connected / off-grid switching. Then, based on resource-side and load-side data, a more suitable power allocation strategy for the target charging station in off-grid mode can be flexibly and accurately determined from both resource and load dimensions. Thus, power supply control of the target charging station can be adapted according to the power allocation strategy, avoiding low-quality power supply control using a fixed power allocation strategy and improving the reliability of power supply control for the target charging station.

[0095] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0096] Based on the same inventive concept, this application also provides a power supply control device for a charging station to implement the power supply control method for the charging station described above. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of one or more power supply control device embodiments for charging stations provided below can be found in the limitations of the power supply control method for charging stations described above, and will not be repeated here.

[0097] In one exemplary embodiment, such as Figure 5 As shown, a power supply control device 500 for a charging station is provided, including: a data acquisition module 502, a strategy determination module 504, and a power supply control module 506, wherein:

[0098] The data acquisition module 502 is used to acquire multi-energy collaborative data of the target charging station when the power supply mode of the target charging station is grid-connected. The multi-energy collaborative data includes grid-side data, resource-side data and load-side data.

[0099] The strategy determination module 504 is used to switch the power supply mode to off-grid mode when the power supply mode switching conditions are met based on grid-side data, and to determine the power allocation strategy matched to the target charging station in off-grid mode based on resource-side data and load-side data.

[0100] The power supply control module 506 is used to control the power supply to the target charging station according to the power distribution strategy.

[0101] In some embodiments, the device further includes a condition determination module, configured to obtain the current grid voltage value and the current frequency from grid-side data; determine the voltage drop magnitude based on the current grid voltage value; determine that the power supply mode switching condition is met when the voltage drop magnitude drops to an amplitude threshold and the current frequency exceeds a preset frequency threshold; and determine that the power supply mode switching condition is not met when the voltage drop magnitude does not drop to an amplitude threshold or when the current frequency is less than or equal to a preset frequency threshold.

[0102] In some embodiments, the strategy determination module 504 is used to obtain the current photovoltaic output of the target charging station from resource-side data, determine the load of charging piles with different priorities in the target charging station from load-side data; determine the matching photovoltaic output scenario based on the current photovoltaic output and the load of charging piles with different priorities; and select the power allocation strategy corresponding to the photovoltaic output scenario from multiple power allocation strategies based on the matching photovoltaic output scenario. The selected power allocation strategy is the power allocation strategy matched by the target charging station in off-grid mode.

[0103] In some embodiments, the strategy determination module 504 is used to superimpose the load of a first-priority charging pile and the load of a second-priority charging pile to obtain a load sum value, wherein the first priority is higher than the second priority; if the current photovoltaic output is greater than or equal to the load sum value, the matching photovoltaic output scenario is determined to be a high photovoltaic output scenario; if the current photovoltaic output is greater than or equal to the load of the first-priority charging pile and the current photovoltaic output is less than the load sum value, the matching photovoltaic output scenario is determined to be a medium photovoltaic output scenario; if the current photovoltaic output is less than the load of the first-priority charging pile, the matching photovoltaic output scenario is determined to be a low photovoltaic output scenario.

[0104] In some embodiments, the apparatus further includes a mode switching module for acquiring new grid-side data, verifying the duration of the grid stability conditions if the new grid-side data is found to meet the grid stability conditions, and switching the off-grid mode back to the grid-connected mode if the duration is greater than or equal to a duration threshold.

[0105] In some embodiments, the mode switching module is used to reduce the energy storage power of the target charging station; after reducing the power to the threshold, the power supply to each charging pile in the target charging station is restored, and the photovoltaic grid-connected power is adjusted at a preset rate.

[0106] Each module in the power supply control device of the aforementioned charging station can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0107] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 6 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media to run. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When the computer program is executed by the processor, it implements a power supply control method for a charging station.

[0108] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0109] In one exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to perform the following steps: when the power supply mode of the target charging station is grid-connected, acquiring multi-energy coordination data of the target charging station, the multi-energy coordination data including grid-side data, resource-side data, and load-side data; when it is determined based on the grid-side data that the power supply mode switching conditions are met, switching the power supply mode to off-grid mode, and determining the power allocation strategy matched to the target charging station in off-grid mode based on the resource-side data and load-side data; and controlling the power supply of the target charging station according to the power allocation strategy.

[0110] In one embodiment, when the processor executes the computer program, it further performs the following steps: obtaining the current grid voltage value and the current frequency from grid-side data; determining the voltage drop magnitude based on the current grid voltage value; determining that the power supply mode switching condition is met when the voltage drop magnitude drops to an amplitude threshold and the current frequency exceeds a preset frequency threshold; and determining that the power supply mode switching condition is not met when the voltage drop magnitude does not drop to an amplitude threshold or when the current frequency is less than or equal to the preset frequency threshold.

[0111] In one embodiment, when the processor executes the computer program, it further performs the following steps: obtaining the current photovoltaic output of the target charging station from resource-side data, and determining the load of charging piles with different priorities in the target charging station from load-side data; determining a matching photovoltaic output scenario based on the current photovoltaic output and the load of charging piles with different priorities; and selecting a power allocation strategy corresponding to the photovoltaic output scenario from multiple power allocation strategies based on the matching photovoltaic output scenario, wherein the selected power allocation strategy is the power allocation strategy matched to the target charging station in off-grid mode.

[0112] In one embodiment, when the processor executes the computer program, it further performs the following steps: superimposing the load of a first-priority charging pile with the load of a second-priority charging pile to obtain a load sum value, wherein the first priority is higher than the second priority; if the current photovoltaic output is greater than or equal to the load sum value, determining the matched photovoltaic output scenario as a high photovoltaic output scenario; if the current photovoltaic output is greater than or equal to the load of the first-priority charging pile and the current photovoltaic output is less than the load sum value, determining the matched photovoltaic output scenario as a medium photovoltaic output scenario; if the current photovoltaic output is less than the load of the first-priority charging pile, determining the matched photovoltaic output scenario as a low photovoltaic output scenario.

[0113] In one embodiment, when the processor executes the computer program, it further performs the following steps: acquiring new grid-side data; if the new grid-side data is found to meet the grid stability conditions, verifying the duration for which the grid stability conditions are met; and if the duration is greater than or equal to a duration threshold, switching the off-grid mode back to the grid-connected mode.

[0114] In one embodiment, when the processor executes the computer program, it also performs the following steps: reducing the energy storage power of the target charging station; and after restoring power supply to each charging pile in the target charging station when the power is reduced to a power threshold, adjusting the photovoltaic grid-connected power at a preset rate.

[0115] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon. When the computer program is executed by a processor, it performs the following steps: when the power supply mode of the target charging station is grid-connected, acquiring multi-energy coordination data of the target charging station, the multi-energy coordination data including grid-side data, resource-side data, and load-side data; when it is determined based on the grid-side data that the power supply mode switching conditions are met, switching the power supply mode to off-grid mode, and determining the power allocation strategy matched to the target charging station in off-grid mode based on the resource-side data and load-side data; and controlling the power supply of the target charging station according to the power allocation strategy.

[0116] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: obtaining the current grid voltage value and the current frequency from grid-side data; determining the voltage drop magnitude based on the current grid voltage value; determining that the power supply mode switching condition is met when the voltage drop magnitude drops to an amplitude threshold and the current frequency exceeds a preset frequency threshold; and determining that the power supply mode switching condition is not met when the voltage drop magnitude does not drop to an amplitude threshold or when the current frequency is less than or equal to the preset frequency threshold.

[0117] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: obtaining the current photovoltaic output of the target charging station from resource-side data, and determining the load of charging piles with different priorities in the target charging station from load-side data; determining a matching photovoltaic output scenario based on the current photovoltaic output and the load of charging piles with different priorities; and selecting a power allocation strategy corresponding to the photovoltaic output scenario from multiple power allocation strategies based on the matching photovoltaic output scenario, wherein the selected power allocation strategy is the power allocation strategy matched by the target charging station in off-grid mode.

[0118] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: superimposing the load of a first-priority charging pile with the load of a second-priority charging pile to obtain a load sum value, wherein the first priority is higher than the second priority; if the current photovoltaic output is greater than or equal to the load sum value, determining the matched photovoltaic output scenario as a high photovoltaic output scenario; if the current photovoltaic output is greater than or equal to the load of the first-priority charging pile and the current photovoltaic output is less than the load sum value, determining the matched photovoltaic output scenario as a medium photovoltaic output scenario; if the current photovoltaic output is less than the load of the first-priority charging pile, determining the matched photovoltaic output scenario as a low photovoltaic output scenario.

[0119] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: acquiring new grid-side data; verifying the duration for which the new grid-side data meets the grid stability conditions; and switching the off-grid mode back to grid-connected mode if the duration is greater than or equal to a duration threshold.

[0120] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: reducing the energy storage power of the target charging station; and after restoring power supply to each charging pile in the target charging station when the power is reduced to a power threshold, adjusting the photovoltaic grid-connected power at a preset rate.

[0121] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps: when the power supply mode of the target charging station is grid-connected, acquiring multi-energy coordination data of the target charging station, the multi-energy coordination data including grid-side data, resource-side data, and load-side data; when it is determined based on the grid-side data that the power supply mode switching conditions are met, switching the power supply mode to off-grid mode, and determining the power allocation strategy matched to the target charging station in off-grid mode based on the resource-side data and load-side data; and controlling the power supply of the target charging station according to the power allocation strategy.

[0122] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: obtaining the current grid voltage value and the current frequency from grid-side data; determining the voltage drop magnitude based on the current grid voltage value; determining that the power supply mode switching condition is met when the voltage drop magnitude drops to an amplitude threshold and the current frequency exceeds a preset frequency threshold; and determining that the power supply mode switching condition is not met when the voltage drop magnitude does not drop to an amplitude threshold or when the current frequency is less than or equal to the preset frequency threshold.

[0123] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: obtaining the current photovoltaic output of the target charging station from resource-side data, and determining the load of charging piles with different priorities in the target charging station from load-side data; determining a matching photovoltaic output scenario based on the current photovoltaic output and the load of charging piles with different priorities; and selecting a power allocation strategy corresponding to the photovoltaic output scenario from multiple power allocation strategies based on the matching photovoltaic output scenario, wherein the selected power allocation strategy is the power allocation strategy matched by the target charging station in off-grid mode.

[0124] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: superimposing the load of a first-priority charging pile with the load of a second-priority charging pile to obtain a load sum value, wherein the first priority is higher than the second priority; if the current photovoltaic output is greater than or equal to the load sum value, determining the matched photovoltaic output scenario as a high photovoltaic output scenario; if the current photovoltaic output is greater than or equal to the load of the first-priority charging pile and the current photovoltaic output is less than the load sum value, determining the matched photovoltaic output scenario as a medium photovoltaic output scenario; if the current photovoltaic output is less than the load of the first-priority charging pile, determining the matched photovoltaic output scenario as a low photovoltaic output scenario.

[0125] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: acquiring new grid-side data; verifying the duration for which the new grid-side data meets the grid stability conditions; and switching the off-grid mode back to grid-connected mode if the duration is greater than or equal to a duration threshold.

[0126] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: reducing the energy storage power of the target charging station; and after restoring power supply to each charging pile in the target charging station when the power is reduced to a power threshold, adjusting the photovoltaic grid-connected power at a preset rate.

[0127] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0128] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0129] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0130] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A power supply control method for a charging station, characterized in that, The method includes: When the power supply mode of the target charging station is grid-connected, acquire the multi-energy coordination data of the target charging station, which includes grid-side data, resource-side data and load-side data; If the power supply mode switching conditions are met based on the grid-side data, the power supply mode is switched to off-grid mode, and the power allocation strategy matched to the target charging station in the off-grid mode is determined based on the resource-side data and the load-side data. The power supply to the target charging station is controlled according to the power allocation strategy.

2. The method according to claim 1, characterized in that, The method further includes: Obtain the current grid voltage value and the current frequency from the grid-side data; Based on the current grid voltage value, determine the voltage drop magnitude; If the voltage drop decreases to an amplitude threshold and the current frequency exceeds a preset frequency threshold, it is determined that the power supply mode switching condition is met. If the voltage drop does not reach the amplitude threshold, or if the current frequency is less than or equal to a preset frequency threshold, it is determined that the power supply mode switching conditions are not met.

3. The method according to claim 1, characterized in that, The step of determining the power allocation strategy matched to the target charging station in the off-grid mode based on the resource-side data and the load-side data includes: The current photovoltaic output of the target charging station is obtained from the resource-side data, and the load of charging piles with different priorities in the target charging station is determined from the load-side data. Based on the current photovoltaic output and the load of charging piles with different priorities, determine the matching photovoltaic output scenario; Based on the matched photovoltaic output scenario, a power allocation strategy corresponding to the photovoltaic output scenario is selected from multiple power allocation strategies. The selected power allocation strategy is the power allocation strategy matched to the target charging station in the off-grid mode.

4. The method according to claim 3, characterized in that, The process of determining the matching photovoltaic output scenario based on the current photovoltaic output and the load of charging piles with different priorities includes: The load of the charging pile with the first priority is superimposed with the load of the charging pile with the second priority to obtain the load sum value, where the first priority is higher than the second priority; If the current photovoltaic output is greater than or equal to the load and value, the matching photovoltaic output scenario is determined to be a high photovoltaic output scenario; If the current photovoltaic output is greater than or equal to the load of the first priority charging pile, and the current photovoltaic output is less than the load and value, the matching photovoltaic output scenario is determined to be a medium photovoltaic output scenario. If the current photovoltaic output is less than the load of the charging pile with the first priority, the matching photovoltaic output scenario is determined to be a low photovoltaic output scenario.

5. The method according to claim 1, characterized in that, After controlling the power supply to the target charging station according to the power allocation strategy, the method further includes: Acquire new grid-side data, and if the new grid-side data is found to meet the grid stability conditions, verify the duration for which the grid stability conditions are met. If the duration is greater than or equal to the duration threshold, the off-grid mode will be switched back to the grid-connected mode.

6. The method according to claim 5, characterized in that, The method further includes: The energy storage capacity of the target charging station is reduced. After the power is reduced to the threshold value, power is restored to each charging pile in the target charging station, and the photovoltaic grid-connected power is adjusted at a preset rate.

7. A power supply control device for a charging station, characterized in that, The device includes: The data acquisition module is used to acquire multi-energy collaborative data of the target charging station when the power supply mode of the target charging station is grid-connected. The multi-energy collaborative data includes grid-side data, resource-side data and load-side data. The strategy determination module is used to switch the power supply mode to off-grid mode when the power supply mode switching conditions are met based on the grid-side data, and to determine the power allocation strategy matched to the target charging station in the off-grid mode based on the resource-side data and the load-side data. The power supply control module is used to control the power supply of the target charging station according to the power allocation strategy.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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