Electricity load type identification method and device, control method and device, equipment and storage medium

Abstract

The invention provides an electrical load type identification method, an electrical load type control method, an electrical load type identification device, electrical load type control equipment and a storage medium. The operation mode of the power supply system is firstly identified, the operation data used for representing the direct current load and the first alternating current load is determined in the off-grid operation mode, and the operation data is analyzed and matched based on the preset electrical load identification strategy, so that the types of various electrical loads can be effectively distinguished. Through the method, operation characteristics of different load types can be established for an alternating current load powered by photovoltaic power and a direct current load in a system under multiple power supply modes (especially an off-grid operation mode), and the problem of inaccurate load identification caused by change of the power supply modes or coexistence of the multiple power supply modes in the prior art is effectively avoided.

Description

Technical Field

[0001] The present invention relates to the field of optical energy storage technology, and in particular to an identification method, control method, device, equipment and storage medium for an electric load type. Background Art

[0002] With the development of distributed renewable energy and DC technology, especially the promotion and application of integrated photovoltaic and storage products, the energy consumption status and mode on the user side have undergone tremendous changes, from the traditional top-down power grid to the distributed and off-grid self-sufficient photovoltaic and storage system, which has put forward higher requirements for the balanced management and flexible control of sources and loads.

[0003] In the application scenario with photovoltaic power supply, since the power supply system adopts an AC / DC hybrid power supply mode, and various types of loads (for example, DC loads, loads powered by energy storage batteries, and AC loads) may be independently powered through different power supply paths (photovoltaic, energy storage, or power grid), the traditional load identification method that relies on AC meters can only monitor the data on the AC side (for example, voltage, current, active power, and reactive power), but cannot collect the operating data on the DC side. Therefore, traditional AC meters can only obtain partial load status information and cannot fully reflect the overall power consumption of the system, resulting in the inability to identify the type and operating status of DC loads or other non-AC loads in multiple power supply modes, resulting in obvious limitations and inaccuracies in the identification of power load types in complex photovoltaic storage systems. Therefore, in the related art, there is a technical problem of inaccurate identification of power load types. Summary of the invention

[0004] The purpose of the present invention is to overcome the above-mentioned technical deficiencies and provide a method, control method, device, equipment and storage medium for identifying the type of power load to solve the technical problem of inaccurate identification of the type of power load in the related art.

[0005] In order to achieve the above technical objectives, the present invention adopts the following technical solutions: In a first aspect, the present invention provides a method for identifying an electric load type, the method comprising: Identify the operating mode of the current power supply system; wherein the power supply system is configured to be powered at least by photovoltaics, and the operating mode includes at least an off-grid operating mode; When the operation mode is off-grid operation, determining first operation data for characterizing the operation state of a DC load and second operation data for characterizing the operation state of a first AC load; wherein the first AC load is an AC load indicated as being preferentially powered by the photovoltaic power supply; The first operating data and the second operating data are identified by using a preset power load identification strategy to obtain at least one power load type of the current power supply system.

[0006] In a second aspect, the present invention provides a flexible control method, the method comprising: Using the above-mentioned method for identifying the power load type, identifying at least one power load type of the current power supply system; wherein the power load type at least includes the type of flexible power load; When there is at least one type of flexible power load, flexible control is performed on the power supply system and / or the load corresponding to the flexible power load based on a preset flexible control strategy.

[0007] In a third aspect, the present invention provides a device for identifying a type of power load, the device comprising: A first identification module, which is used to identify the operation mode of the current power supply system; wherein the power supply system is configured to be powered at least by photovoltaic power, and the operation mode includes at least an off-grid operation mode; A determination module, which is used to determine, when the operation mode is off-grid operation, first operation data for characterizing the operation state of a DC load and second operation data for characterizing the operation state of a first AC load; wherein the first AC load is an AC load indicated as being preferentially powered by the photovoltaic power supply; The second identification module is used to identify the first operating data and the second operating data through a preset power load identification strategy to obtain at least one power load type of the current power supply system.

[0008] In a fourth aspect, the present invention provides an electronic device comprising: a memory, and one or more processors communicatively connected to the memory; the memory stores instructions executable by the one or more processors, and the instructions are executed by the one or more processors so that the one or more processors implement the above-mentioned method.

[0009] In a fifth aspect, the present invention provides a computer-readable storage medium, wherein the computer program is stored in the computer-readable storage medium, and the computer program implements the above method when executed by a processor.

[0010] Beneficial effects: The present invention can effectively distinguish the types of various power loads by first identifying the operating mode of the power supply system, determining the operating data for characterizing the DC load and the first AC load in the off-grid operating mode, and analyzing and matching these operating data based on a preset power load identification strategy. Through this method, it is possible to establish operating characteristics of different load types for the AC load powered by photovoltaic power and the DC load in the system under various power supply modes (especially the off-grid operating mode), effectively avoiding the problem of inaccurate load identification caused by changes in the power supply mode or the coexistence of multiple power supply modes in the prior art. At the same time, the present invention can dynamically track the load state during the actual load operation process, and provide accurate load type information by accurately identifying the first operating data and the second operating data, thereby ensuring that the system can perform load regulation and energy optimization in complex power supply scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 It is a flowchart of a method for identifying a power load type provided by an embodiment of the present invention; Figure 2 It is a flowchart of a method for identifying a power load type provided by an embodiment of the present invention; Figure 3 It is a flowchart of a method for identifying a power load type provided by an embodiment of the present invention; Figure 4 is a flow chart of a flexible control method provided by an embodiment of the present invention; Figure 5 is a block diagram of an intelligent optical storage device provided by an embodiment of the present invention; Figure 6 It is a block diagram of the application of electric meter load identification in the related technology; Figure 7 It is an application block diagram of the method for identifying the type of power load provided by the present invention; Figure 8 is a circuit diagram of an intelligent light storage device provided by an embodiment of the present invention; Fig. 9 is a block diagram of a device for identifying the type of power load used in an embodiment of the present invention; Fig.10 It is a block diagram of an electronic device used in an embodiment of the present invention. DETAILED DESCRIPTION

[0012] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0013] Overview: In related technologies, photovoltaic and energy storage systems usually support both AC and DC loads, and these loads can be powered by photovoltaic power generation and energy storage batteries. This AC / DC hybrid power supply mode is different from a single AC power supply system. The AC meter in related technologies only monitors the power data of the AC end, such as voltage, current, active power and reactive power. However, in scenarios with DC loads, such as Figure 6 As shown in the figure, the AC meter cannot obtain relevant data on the DC side, which means that it can only reflect part of the system information, but cannot fully describe the overall power consumption of the system. Moreover, in a photovoltaic-storage integrated system, the load may include different types of equipment, such as DC loads directly powered by photovoltaics, equipment powered by energy storage batteries, and equipment powered by AC / DC converters. The AC meter can only detect equipment information related to the power grid or AC power supply. Therefore, for these loads powered by other means (such as DC, energy storage, etc.), the AC meter cannot effectively sense them and it is difficult to identify the load category and its specific operating status.

[0014] It is understandable that the photovoltaic storage system can be operated in grid-connected mode or in off-grid mode. The AC meter is mainly used to detect the state of power interaction between the grid and the system when it is in grid-connected mode. In off-grid mode, the system's power no longer flows through the grid, but is supplied by photovoltaic power generation and energy storage devices. At this time, the AC meter no longer obtains valid power data, so it is impossible to judge the system's load status through the reading of the AC meter.

[0015] Therefore, in the application scenario with photovoltaic power supply, there is a technical problem of inaccurate identification of power load type. Figure 7As shown, the method for identifying the type of power load provided in this embodiment can effectively distinguish the types of various power loads by first identifying the operation mode of the power supply system, determining the operation data for characterizing the DC load and the first AC load in the off-grid operation mode, and analyzing and matching these operation data based on the preset power load identification strategy. Through this method, it is possible to establish the operation characteristics of different load types for the AC load powered by photovoltaic power and the DC load in the system under various power supply modes (especially the off-grid operation mode), effectively avoiding the problem of inaccurate load identification caused by the change of power supply mode or the coexistence of multiple power supply modes in the prior art. At the same time, this method can dynamically track the load state during the actual load operation process, and provide accurate load type information by accurately identifying the first operation data and the second operation data, thereby ensuring that the system can perform load regulation and energy optimization in complex power supply scenarios. This embodiment improves the accuracy and stability of power load identification in complex power supply scenarios, and provides a reliable data basis and decision support for the optimization of subsequent load scheduling and energy management strategies.

[0016] Example like Figure 1 As shown, this embodiment provides a method for identifying the type of power load, which can be applied to an intelligent photovoltaic storage machine, which can be configured in an application scenario of hybrid power supply through photovoltaic power supply, energy storage battery power supply and grid power supply. The method may include: Step S102: identifying the operation mode of the current power supply system; wherein the power supply system is configured to be powered at least by photovoltaics, and the operation mode includes at least an off-grid operation mode.

[0017] In this implementation, the identification action may be represented by collecting the operating status data of the current power supply system, and then determining the operating mode of the current power supply system.

[0018] Specifically, the operating status data may be the DC voltage output by the photovoltaic module. The intelligent photovoltaic storage device may determine whether the voltage threshold of the photovoltaic module has been reached. If the voltage threshold is higher than the voltage threshold, it indicates that the photovoltaic module can supply power independently, and the power supply system may be in off-grid mode.

[0019] The operating status data may also be AC ​​current data or AC voltage data provided by the power grid obtained from the communication interface. If a specific data value is obtained, it indicates that the power supply system may be in grid-connected mode at this time. If no specific data value is obtained or the data value obtained is 0, it indicates that the power supply system may be in off-grid mode at this time.

[0020] The operation status data may also be the on / off status of the grid-connected relay. For example, the intelligent solar storage device may collect the on / off status of the current grid-connected relay. When the grid-connected relay is off, it indicates that the power supply system may be in off-grid mode.

[0021] In this embodiment, the power supply system is a power supply system configured to be powered at least by photovoltaics. It is understandable that the power supply system can be powered by the power grid, and the power supply system can also be powered by other clean energy. For example, it can be powered by wind power generation. It can be powered by hydropower generation. The power supply system can also be powered by energy storage batteries. The electric energy in the energy storage battery can be provided by the power grid or by photovoltaic modules. It is understandable that photovoltaic modules can be configured in the power supply system to generate electricity.

[0022] In this embodiment, the power supply system can be applied in a civilian application scenario, for example, in one or more home scenarios, and the power supply system can supply power to loads such as electric lights, air conditioners or refrigerators in the home. The power supply system can be applied in an industrial application scenario, for example, it can be a factory, warehouse, office building or other industrial application scenario. It can provide power for industrial air conditioners, production equipment, compressors, data servers, control systems and security monitoring devices in these application scenarios.

[0023] In this embodiment, the operation mode can be represented as a specific working state of the power supply system. The operation mode may include an off-grid operation mode. The off-grid operation mode can be represented as a mode in which the power supply system is completely disconnected from the power grid and only relies on photovoltaic power generation (and energy storage batteries) to power local loads. In this mode, all loads in the power supply system are completely dependent on the power supply of photovoltaic modules and energy storage batteries. When the power generation of the photovoltaic module is sufficient, the photovoltaic module can directly power the load, and the excess power can be stored in the energy storage battery. When the power generation of the photovoltaic module is insufficient, the energy storage battery can be powered together with the photovoltaic module.

[0024] The operation mode may also include a grid-connected operation mode. The grid-connected operation mode may be represented as the power supply system being connected to the power grid and realizing the supply or allocation of electric energy through the power grid. In the grid-connected operation mode, the power supply system may perform two-way interaction of electric energy with the power grid (that is, it may draw electricity from the power grid or send electricity back to the power grid) according to the real-time situation of power supply and load demand. It is understandable that in the grid-connected operation mode, the photovoltaic module, the energy storage battery and the power grid together constitute the source of electric energy supply for the power supply system. More specifically, in the grid-connected operation mode, when the power generation of the photovoltaic module is sufficient, the power supply system may give priority to using photovoltaic power to power the load, and the remaining power may be stored in the energy storage battery or directly fed to the power grid to obtain economic benefits. When the power generation of the photovoltaic module is insufficient, the power supply system may automatically switch to power supply by the energy storage battery or supplement power from the power grid.

[0025] The operation mode may also include a hybrid operation mode. The hybrid operation mode may be represented as a working mode in which the power supply system can dynamically adjust the power supply strategy according to the comprehensive situation of photovoltaic power generation, energy storage battery power and grid status, and flexibly switch between grid-connected mode and off-grid mode. More specifically, when the power generation of the photovoltaic module is sufficient, the power supply system may give priority to the grid-connected mode to make full use of the photovoltaic power; when the power generation of the photovoltaic module is insufficient or the grid voltage is abnormal, the power supply system may automatically switch to the off-grid mode and give priority to using the energy storage battery for power supply.

[0026] In this embodiment, the action of identifying the operating mode of the current power supply system may be triggered at a fixed time, for example, the identification of the operating mode of the current power supply system may be triggered every five or ten minutes. The action of identifying the operating mode of the current power supply system may also be triggered based on an event. For example, when the power generation of the photovoltaic module, the power of the energy storage battery, or the power supply status of the grid changes significantly (such as a sudden increase or decrease in the power generation of the photovoltaic module, the power of the energy storage battery reaches a set threshold, or the grid is powered off, etc.), the intelligent photovoltaic storage machine will be triggered to re-identify the current operating mode. The intelligent photovoltaic storage machine can also perform identification operations based on external instructions or requests.

[0027] like Figure 5 As shown, in a possible implementation, the intelligent light storage device may include: The AC side U / I / P / Q acquisition module is used to collect and monitor the electrical parameters of the AC load (such as voltage U, current I, active power P, reactive power Q) in real time. By detecting these parameters, the module can identify the operating status of the AC load (such as on, off or power fluctuation, etc.), and pass these data to the MCU main control module as the basis for subsequent load identification and power supply mode scheduling. The AC load can be an AC load that is preferentially powered by the photovoltaic power supply. For example, it can be an important load that does not lose power when running off the grid, and some loads that can participate in flexible power regulation. Specifically, this type of AC load can be preferentially powered by photovoltaic power generation or energy storage batteries, and will not be powered off when the power supply system switches to off-grid mode. This type of AC load can not only maintain non-power-off operation in the case of power outage or off-grid mode, but also can be flexibly power-regulated by the intelligent photovoltaic storage machine to ensure the normal operation of critical loads when the power supply is tight. In the application scenario of the home, the AC load can be a refrigerator, air conditioner or lighting, etc. When the power supply capacity is insufficient, the intelligent photovoltaic storage machine can dynamically adjust the power of these loads through a flexible control strategy. For example, reduce the operating power of the air conditioner or enter energy-saving mode to ensure that the power can support the stable operation of all critical loads for a long time.

[0028] AC / DC module and DC / DC module, this module mainly realizes AC-DC conversion and power output size adjustment.

[0029] Photovoltaic modules and battery modules, which mainly realize power generation and storage to ensure that the system can operate without power loss when off-grid.

[0030] DC side U / I / P / Q acquisition module, which mainly collects the DC interface electrical parameters of the intelligent photovoltaic storage machine.

[0031] The MCU main control module may be preset with a method for identifying the type of power load provided in this embodiment. For example, the DC load power and load operation status may be calculated by P=U*I.

[0032] Communication module, which can communicate with the AC meter to obtain the electrical data provided by the power grid to the power supply system, such as circuit, voltage and power, etc. The AC meter can transmit real-time data to the MCU main control module through the communication module, so that the intelligent solar storage machine can accurately sense the voltage, current, active power and reactive power of the power grid, so as to make a comprehensive judgment on the state of the power grid. Figure 8 As shown, in a specific embodiment, the intelligent light storage device may include: The AC input interface and the AC filter module are used to connect the first AC load. The AC filter module includes an AC filter inductor L1 and a filter capacitor C0, which are used to filter out high-frequency interference signals and electromagnetic interference in the input AC current to ensure the stability of the input AC current.

[0033] AC / DC conversion module, which converts the input AC power into DC power through power switch tubes (Q1, Q2, Q3, Q4) and filter inductor L1. The AC / DC conversion part can adopt a full-bridge or half-bridge circuit topology. The control signal (PWM1-4) comes from the main control module MCU, and the power conversion is realized through precise switch control. The filter capacitor C1 can be used to smooth the rectified DC current and reduce ripple and current pulsation.

[0034] DC / DC conversion module, which is used to realize the step-up and step-down conversion of DC voltage to meet the power supply requirements of different DC loads. A bidirectional DC / DC conversion circuit composed of transformer coupling T1 and power switch tubes (Q5, Q6, Q7, Q8) is used. Inductor L2 and capacitor C2 are used for filtering and energy storage to ensure the stability of the output DC voltage.

[0035] DC output interface: This module is used to connect DC load devices and output DC voltage and current signals after DC / DC conversion, which can provide stable power supply for DC loads.

[0036] MCU main control module, which is the core control unit of the entire intelligent optical storage machine.

[0037] AC current sampling circuit, this module monitors the AC current signal in real time through the sampling resistor R1 and the operational amplifier U1, converts it into a standard voltage signal, and transmits it to the MCU main control module for data processing.

[0038] DC current sampling circuit, this module detects DC current through sampling resistor R2, and the sampling signal is transmitted to the DC current sampling circuit module for real-time monitoring of the DC current.

[0039] DC voltage sampling circuit, this module collects the DC output voltage to ensure that the system can monitor the working status of the DC load in real time in off-grid mode.

[0040] Step S104: when the operation mode is off-grid operation, determine first operation data for characterizing the operation state of a DC load and second operation data for characterizing the operation state of a first AC load; wherein the first AC load is an AC load indicated as being preferentially powered by the photovoltaic power supply.

[0041] In this implementation, the first operating data may include voltage data, current data, and power data of the DC load.

[0042] In this implementation, the second operating data may include voltage data, current data and power data of the first AC load.

[0043] In some embodiments, the first operation data may also include the power factor of the DC load, the load operation time, the number of load starts and stops, and the load usage behavior data. It is understood that the power factor can be expressed as the ratio of active power to apparent power, expressed as the ratio of the active power actually consumed by the load to the total power (which can be expressed as a decimal or a percentage).

[0044] In some implementations, the second operating data may also include the power factor of the first AC load, load operating time, load start and stop times, and load usage behavior data.

[0045] In some embodiments, the second operation data may also include frequency data and phase angle data of the first AC load, etc. It is understandable that the frequency data may represent the frequency value of the AC power supply during the operation of the first AC load. Phase angle data refers to the phase difference between the AC voltage and the current. In this embodiment, by incorporating parameters such as the frequency data and phase angle data of the first AC load into the second operation data, the recognition accuracy and differentiation ability of the first AC load type and its operating state can be further improved, thereby more comprehensively and accurately describing the electrical characteristics of the load. Frequency and phase angle are important characteristic parameters of inductive, capacitive, and resistive loads. By collecting and analyzing these data, AC loads of different properties (such as motors, compressors, lighting equipment, etc.) can be effectively distinguished. Inductive loads (such as motors) usually have a large phase lag, while capacitive loads (such as some lighting equipment) show a phase lead. By analyzing the phase angle data, the electrical properties of the load can be more accurately identified, thereby improving the ability to distinguish different types of AC loads. In this embodiment, the DC load can be represented as an electrical device powered by a DC power supply (for example, photovoltaic module power generation, energy storage battery, etc.). The DC loads may include: lighting equipment, DC fans, DC air conditioners, DC refrigerators, DC washing machines, laptops, smart phones and their chargers, etc. Specifically, lighting equipment may include DC LED lamps and DC lamp tubes, etc. DC refrigerators can be powered directly by energy storage batteries or photovoltaic DC power sources. DC washing machines are equipped with DC motors and can operate normally in low-voltage DC environments. The DC loads may also include: energy storage batteries, electric vehicles and their charging equipment. It is understandable that the energy storage battery itself, as a DC power supply device, is both a part of the power supply system and can be used as a DC load in the power supply system to manage the charging of electrical energy.

[0046] In this embodiment, the first AC load can be represented as an AC load that can continue to maintain power supply when the power supply system is off-grid. The AC load can be a device that has high requirements for power supply continuity and needs to prioritize operation. Therefore, the first AC load can be an AC load that is preferentially powered by the photovoltaic power supply. This type of load will not only not lose power due to power outages in the off-grid mode, but also have the ability to participate in flexible power regulation, so that when the power supply is insufficient, the basic operating state can be maintained through dynamic power regulation. Specifically, the priority to be powered by the photovoltaic power supply can be represented as the first AC load being preferentially powered by photovoltaic power supply when the power supply is off-grid. The priority to be powered by the photovoltaic power supply can also be represented as the first AC load being preferentially powered by photovoltaic power supply when the power supply is connected to the grid. In off-grid mode, the first AC load is a load that needs to be prioritized in the power supply system. When the power supply is limited (such as insufficient power in the energy storage battery), the power supply system will prioritize the first AC load, and limit or temporarily cut off other secondary loads (such as entertainment equipment, etc.) to ensure that the first AC load can continue to operate stably. The first AC load can have a flexible power regulation capability, can be controlled by an intelligent photovoltaic storage device, and dynamically adjust the operating power. For example, when the power supply is insufficient, the first AC load can reduce power consumption (for example, the air conditioner can be switched to energy-saving mode or the operating power can be lowered) to adapt to the current power supply capacity of the power supply system and maximize its operating time. The load characteristic curve of the first AC load (such as the curve of changes in parameters such as voltage, current, and power over time) usually has a more obvious periodicity or characteristic. For example, the air conditioner will have an obvious power peak when it starts, and then gradually run smoothly. The current and voltage waveform characteristics of lighting equipment are relatively stable, and fluctuate significantly when starting and stopping.

[0047] In this embodiment, the first AC load may include an air conditioner, a refrigerator, and an intelligent lighting system. It is understandable that the air conditioner, as a flexible control load, can dynamically adjust the cooling / heating power according to the power supply capacity of the power supply system. Moreover, the usage habits of air conditioners are often clear. For example, air conditioners are usually turned on in the afternoon or evening in summer and enter energy-saving mode at night. The refrigerator requires continuous power supply around the clock to maintain a constant internal temperature. Because its working mode is relatively stable, the refrigerator can dynamically adjust power consumption according to changes in internal temperature. In industrial application scenarios, the first AC load may include industrial air conditioners and ventilation equipment.

[0048] In this embodiment, the determined action can be expressed as determining the first operating data and the second operating data through actions such as collection, analysis and processing. Specifically, the intelligent photoelectric storage machine can collect the current and voltage of the DC load and the first AC load in real time through an acquisition module (for example, it can be an electrical parameter acquisition module on the AC side and an electrical parameter acquisition module on the DC side). The intelligent photoelectric storage machine can also calculate power through a control module (for example, it can be an MCU) and the collected current and voltage. The intelligent photoelectric storage machine can also perform preliminary processing and analysis (for example, filtering, normalization, data conversion, etc.) on the data collected by the acquisition module through the control module to remove possible noise or abnormal data. The intelligent photoelectric storage machine can also perform feature extraction on the current, voltage and power data through the control module. For example, the power factor and phase angle, etc. can be extracted.

[0049] In a specific embodiment, Figure 5 As shown. The voltage and current data of the DC load can be collected by the DC side U / I / P / Q acquisition module, and the power value of the DC load can be calculated based on the P=U×I formula. The voltage and current data of the first AC load can be collected by the AC side U / I / P / Q acquisition module, and the power value of the first AC load can be calculated based on the P=U×I formula. Step S106: For the first operating data and the second operating data, identify them through a preset power load identification strategy to obtain at least one power load type of the current power supply system.

[0050] In this embodiment, the power load identification strategy may be a rule-based identification strategy or a model-based identification strategy.

[0051] In this embodiment, the rule-based identification strategy may be a power load identification rule base. Specifically, the rule-based identification strategy may be expressed as pre-storing the characteristics of the load type (for example, the waveform of the voltage and current, the power factor, the start-stop behavior, etc.) in the power load identification rule base (the power load identification rule base may be configured in the control module), and comparing the first operating data and the second operating data with the characteristics in the power load identification rule base to determine the power load type. The power load identification rule base may be expressed as a set of rules that stores the operating characteristics of multiple load types. Each rule may include one or more data that can reflect the characteristics of the load (for example, current, voltage, power, etc.) and a characteristic curve or state description of these data changing over time.

[0052] Specifically, the power load identification rule base may include a starting current characteristic rule (for example, it may be a current peak value when the load starts). More specifically, the starting current characteristic rule may describe parameters such as the current peak value, current rise rate, and starting duration of the load (which may be a DC load or an AC load) when starting. For example, air conditioners and refrigerators will show a high current peak value when starting, while electric lights will not have significant current fluctuations.

[0053] Specifically, the power load identification rule base may include steady-state operation characteristic rules (for example, power factor, phase angle, power fluctuation characteristics, etc. when the load is in steady state). More specifically, the steady-state operation characteristic rules may describe the steady-state characteristics of the load (which may be a DC load or an AC load) under normal working conditions, such as steady-state power factor, power fluctuation amplitude, phase angle change, etc. A running air conditioner often has a stable power fluctuation characteristic and a high power factor, while a lamp usually maintains a stable power and phase angle.

[0054] Specifically, the power load identification rule base may include start-stop behavior characteristic rules (for example, the start-stop pattern or the number of start-stop times of the load in a day). More specifically, the start-stop behavior characteristic rules may describe the start-stop pattern and behavior pattern of the load (which may be a DC load or an AC load) in a day or a period of time. For example, refrigerators usually exhibit periodic start-stop behavior (such as starting every tens of minutes), while other loads (such as air conditioners) are more dependent on environmental conditions (such as temperature).

[0055] Specifically, the power load identification rule base may also include load characteristic curve rules (for example, the current-power change curve, power-time curve, etc. of the load). The load characteristic curve rule may identify the load type based on the current-power, power-time, or power-voltage curves. For example, the power curve of a motor load during startup and steady-state operation is completely different from that of a lighting load, so they can be distinguished by comparing the characteristic curves.

[0056] In this embodiment, the power load identification rule base is pre-established. The features of multiple DC loads and AC loads can be collected in advance to generate the power load identification rules of the power load identification rule base. Specifically, when constructing the power load identification rule base, the operating data of multiple load types can be collected and analyzed for a long time to extract the characteristic parameters of each load during startup, steady state, and shutdown, and these data can be calibrated as identification features of different loads. For example, by collecting the startup current, operating power, and shutdown behavior of the air conditioner for a long time, its typical current-time variation curve can be obtained, and the "air conditioner load startup characteristic rule" can be generated based on the curve.

[0057] In this implementation, the power load identification rule base may be dynamically updated.

[0058] In this embodiment, when the first operating data and the second operating data are identified using a power load identification rule library, the first operating data and the second operating data can be matched with each power load identification rule in the power load identification rule library. When one or more power load identification rules are hit, it indicates that there is a power load type corresponding to the hit power load identification rule in the current power supply system.

[0059] In this embodiment, matching can be performed based on a threshold value. For example, it can be determined whether the first operating data and the second operating data (for example, current, voltage or power, or feature parameters obtained by extracting features from current, voltage or power) are within a threshold range predefined by the power load identification rule. If they are within a threshold range predefined by a power load identification rule, it means that the power load identification rule is hit. The threshold value can be a similarity threshold value.

[0060] In this implementation, it is obtained that at least one power load type of the current power supply system is represented as the intelligent photovoltaic storage machine can output the power load type as the identification result.

[0061] In this embodiment, the model-based identification strategy can be expressed as using a pre-trained power load identification model (for example, a machine learning model or a deep learning model) to identify the type of the current load. Specifically, the power load identification model can be trained through a large amount of historical data (for example, current data, voltage data, power data of various historical loads, and feature data obtained by feature extraction of these data).

[0062] In this embodiment, the power load identification model may be a power load identification model based on a support vector machine (SVM).

[0063] In this embodiment, the power load identification model may be a power load identification model based on a decision tree.

[0064] In this embodiment, the power load identification model may be a power load identification model based on cluster analysis.

[0065] In this embodiment, the power load identification model may be a power load identification model based on a convolutional neural network model.

[0066] The method for identifying the type of power load provided in this embodiment can effectively distinguish the types of various power loads by first identifying the operation mode of the power supply system, determining the operation data for characterizing the DC load and the first AC load in the off-grid operation mode, and analyzing and matching these operation data based on the preset power load identification strategy. Through this method, it is possible to establish the operation characteristics of different load types for the AC load powered by photovoltaic power and the DC load in the system under various power supply modes (especially the off-grid operation mode), effectively avoiding the problem of inaccurate load identification caused by the change of power supply mode or the coexistence of multiple power supply modes in the prior art. At the same time, this method can dynamically track the load state during the actual load operation process, and provide accurate load type information by accurately identifying the first operation data and the second operation data, thereby ensuring that the system can perform load regulation and energy optimization in complex power supply scenarios. This embodiment improves the accuracy and stability of power load identification in complex power supply scenarios, and provides a reliable data basis and decision support for the optimization of subsequent load scheduling and energy management strategies.

[0067] like Figure 2 As shown, in some embodiments, the first operating data includes at least current data, voltage data and power data of the DC load, and the second operating data includes at least current data, voltage data and power data of the first AC load; the step of determining the first operating data for characterizing the operating state of the DC load and the second operating data for characterizing the operating state of the first AC load may include: Step S1042: collecting current data and voltage data of the DC load and current data and voltage data of the first AC load.

[0068] Step S1044: Calculate the power data of the DC load based on the current data and the voltage data of the DC load, and calculate the power data of the first AC load based on the current data and the voltage data of the first AC load.

[0069] In this embodiment, by collecting the current data and voltage data of the DC load and the first AC load, and calculating the power data of the DC load and the first AC load based on these data, a comprehensive and accurate characterization of the load operation status can be achieved. Compared with the method of relying on a single electrical parameter (such as current or voltage) for load identification, this embodiment can more accurately reflect the actual working state of the load and its power consumption characteristics by introducing a joint analysis of the three key parameters of voltage, current and power, thereby improving the accuracy and reliability of load identification. In addition, by accurately calculating the power data of DC and AC loads, the power characteristics of different loads during the start-stop process can be further distinguished, which helps the power supply system to more efficiently identify the load type in a complex load environment (especially in an off-grid scenario where multiple types of loads coexist), optimize energy distribution and management strategies, and ensure the stability and economy of the power supply system operation.

[0070] In some implementations, the step of collecting the current data and voltage data of the DC load may include: The current data of the DC load is collected from a preset DC interface through a preset DC current sampling circuit.

[0071] The DC current sampling circuit can be a sampling circuit based on a current sampling resistor, or a current sampling circuit based on a Hall effect sensor, and the voltage data of the DC load is collected from a preset DC interface through a preset DC voltage sampling circuit.

[0072] In this embodiment, the DC voltage sampling circuit can be a voltage sampling circuit based on resistor voltage division or a voltage sampling circuit based on isolation amplification. In this embodiment, the current data and voltage data of the DC load are respectively collected from the DC interface through the preset DC current sampling circuit and DC voltage sampling circuit, so that the DC load operation status can be accurately monitored and the electrical parameters can be obtained in real time. Compared with the traditional single parameter acquisition method, this embodiment can improve the accuracy and stability of data acquisition through an independently designed sampling circuit, avoid data inconsistency problems caused by signal interference or sampling errors, and thus ensure the integrity of current and voltage data.

[0073] In some implementations, the step of collecting current data and voltage data of the first AC load may include: The current data of the first AC load is collected from a preset AC interface through a preset AC current sampling circuit.

[0074] In this embodiment, the AC current sampling circuit can be a current sampling circuit based on a current transformer or an AC current sampling circuit based on a sampling resistor. The voltage data of the first AC load is collected from a preset AC interface through a preset AC voltage sampling circuit.

[0075] In this embodiment, the AC voltage sampling circuit can be a voltage sampling circuit based on resistor voltage division. In this embodiment, the current data and voltage data of the first AC load are respectively collected from the AC interface through the preset AC current sampling circuit and AC voltage sampling circuit, so that high-precision monitoring and real-time data collection of the AC load operating status can be achieved. Compared with the traditional comprehensive parameter collection method, this embodiment can effectively improve the sensitivity and anti-interference ability of current and voltage data collection through the independent AC current and voltage sampling circuit design, thereby ensuring the collection accuracy and data stability of AC electrical parameters.

[0076] In some embodiments, the preset power load identification strategy is a power load identification rule base, and the power load identification rule base is configured with at least one power load identification rule; the step of identifying the first operating data and the second operating data by the preset power load identification strategy to obtain the power load type of the current power supply system includes: Step S1062: Identify the first operating data and the second operating data based on at least one power load identification rule in the power load identification rule base to obtain the power load type of the current power supply system.

[0077] The power load identification rule base may include a startup current characteristic rule (for example, it may be a current peak value when the load is started). More specifically, the startup current characteristic rule may describe parameters such as the current peak value, current rise rate, and startup duration of the load (which may be a DC load or an AC load) when it is started. For example, air conditioners and refrigerators will show a high current peak value when they are started, while electric lights will not have significant current fluctuations.

[0078] Specifically, the power load identification rule base may include steady-state operation characteristic rules (for example, power factor, phase angle, power fluctuation characteristics, etc. when the load is in steady state). More specifically, the steady-state operation characteristic rules may describe the steady-state characteristics of the load (which may be a DC load or an AC load) under normal working conditions, such as steady-state power factor, power fluctuation amplitude, phase angle change, etc. A running air conditioner often has a stable power fluctuation characteristic and a high power factor, while a lamp usually maintains a stable power and phase angle.

[0079] Specifically, the power load identification rule base may include start-stop behavior characteristic rules (for example, the start-stop pattern or the number of start-stop times of the load in a day). More specifically, the start-stop behavior characteristic rules may describe the start-stop pattern and behavior pattern of the load (which may be a DC load or an AC load) in a day or a period of time. For example, refrigerators usually exhibit periodic start-stop behavior (such as starting every tens of minutes), while other loads (such as air conditioners) are more dependent on environmental conditions (such as temperature).

[0080] Specifically, the power load identification rule base may also include load characteristic curve rules (for example, the current-power change curve, power-time curve, etc. of the load). The load characteristic curve rule may identify the load type based on the current-power, power-time, or power-voltage curves. For example, the power curve of a motor load during startup and steady-state operation is completely different from that of a lighting load, so they can be distinguished by comparing the characteristic curves.

[0081] In this embodiment, the power load identification rule base is pre-established. The features of multiple DC loads and AC loads can be collected in advance to generate the power load identification rules of the power load identification rule base. Specifically, when constructing the power load identification rule base, the operating data of multiple load types can be collected and analyzed for a long time to extract the characteristic parameters of each load during startup, steady state, and shutdown, and these data can be calibrated as identification features of different loads. For example, by collecting the startup current, operating power, and shutdown behavior of the air conditioner for a long time, its typical current-time variation curve can be obtained, and the "air conditioner load startup characteristic rule" can be generated based on the curve.

[0082] In this implementation, the power load identification rule base may be dynamically updated.

[0083] In this embodiment, when the first operating data and the second operating data are identified using a power load identification rule library, the first operating data and the second operating data can be matched with each power load identification rule in the power load identification rule library. When one or more power load identification rules are hit, it indicates that there is a power load type corresponding to the hit power load identification rule in the current power supply system.

[0084] In this implementation, the power load type may be a plurality of preset power load types.

[0085] Specifically, the load can be classified based on its own characteristics, such as resistive load, inductive load, capacitive load and non-linear load. Resistive load means that its main power consumption is the conversion of electrical energy into heat energy, and the current and voltage are consistent in phase. Inductive load refers to a load containing coils or inductive elements, which requires a large impact current when starting, and the current lags behind the voltage during steady-state operation. Capacitive load refers to a load that contains capacitor elements inside, and its current leads the voltage. Non-linear load means that the current and voltage waveforms are not sinusoidal and have higher harmonic components.

[0086] Specifically, loads can be classified based on their importance, such as critical loads and non-critical loads. Critical loads refer to loads that have extremely high requirements for power supply continuity and may cause safety risks or serious economic losses once power is lost. Non-critical loads refer to loads that will not cause significant impacts if power is lost and can be shut down or power is limited when power supply is insufficient.

[0087] In this embodiment, by identifying the first operating data and the second operating data based on at least one power load identification rule in the power load identification rule base, the pre-stored power load characteristic rules can be effectively used to achieve accurate judgment of the current load type. Compared with the traditional identification method that relies on a single electrical parameter, this embodiment can perform fine-grained analysis on different types of loads through comprehensive matching of multiple load identification rules, thereby improving the accuracy and reliability of load identification. At the same time, by using the power load identification rule base for identification, the most appropriate rules can be dynamically matched according to different load characteristics, and the identification strategy can be automatically adjusted according to changes in real-time data, thereby enhancing the system's adaptability to complex and diverse loads, avoiding identification deviations caused by complex load types, and ensuring that the system can accurately distinguish between load types in a multi-load environment, thereby providing reliable data support for subsequent energy management and load regulation.

[0088] like Figure 3 As shown, in some embodiments, the power load identification rule base includes: a load characteristic curve library, in which at least one load characteristic curve is configured; the step of performing identification on the first operating data and the second operating data based on the power load identification rule base to obtain the power load type of the current power supply system may include: Step S10622: Generate a first total operation curve according to the first operation data and the second operation data; wherein the first total operation curve is used to represent the total operation curve at the current moment.

[0089] In this embodiment, the first total operation curve may be an overall electrical characteristic curve representing the operating status of each DC load and the first AC load in the system at the current moment. The first total operation curve may be a curve reflecting the overall status of the system at the current moment generated by superimposing, integrating or weighting the real-time data of multiple loads. Each total operation curve may be able to describe the value change of a certain data (for example, current, voltage or power, etc.) at different time points, thereby showing the load characteristics and power consumption of the system at the current moment.

[0090] In this embodiment, the generated action can be expressed as first generating various characteristic curves, and then combining to generate the first total operation curve. Specifically, the first operation data (DC load data) and the second operation data (first AC load data) are arranged according to the time series to generate multiple characteristic curves, such as "DC current-time curve", "AC current-time curve", "DC power-time curve" and "AC power-time curve". The DC load curve and the first AC load curve are weighted combined or accumulated to obtain a first total operation curve representing the overall load state of the system at the current moment. The first total operation curve can reflect the comprehensive electrical characteristics of all DC and AC loads on an overall time axis, thereby effectively describing the overall load status of the system at the current moment. Since the power consumption characteristics and start-stop behaviors of DC loads and AC loads are different, the first total operation curve can reflect the superposition effect of these different characteristics, which helps to identify the operation mode of a specific load while comprehensively judging the overall system state.

[0091] Step S10624: Generate a target operating curve based on the first total operating curve and a pre-stored second total operating curve; wherein the second total operating curve is a total operating curve before the first total operating curve.

[0092] In this embodiment, the generated action can be expressed as extracting the difference characteristics of the two curves on the same time axis based on the first total operation curve at the current moment and the second total operation curve at the previous moment through mathematical operation or feature analysis, thereby generating a target operation curve that reflects the load change characteristics at the current moment. The target operation curve can indicate the increment or change trend of the load state, which helps to identify new load access, state changes of existing loads (such as start-stop or power fluctuations), and the combined impact between different loads. The generation action can be completed by simple difference operations (such as curve subtraction) or other complex data fusion algorithms.

[0093] In this embodiment, the step of generating a target operating curve based on the first total operating curve and the pre-stored second total operating curve may specifically include: first, performing curve data alignment. Before generating the target operating curve, it is necessary to ensure that the first total operating curve at the current moment is consistent with the second total operating curve at the previous moment on the time axis, and the data corresponding to each time point can be directly calculated and compared. Then, the difference operation is directly performed on the data of the two total operating curves at the same time point to generate the target operating curve. For some complex load scenarios, there may be multiple loads changing at the same time or complex start-stop behaviors, and simple subtraction cannot accurately reflect the characteristics of each load. Therefore, the incremental feature analysis method can be introduced to conduct an in-depth analysis of the changing characteristics of the two total operating curves.

[0094] In this implementation, the first total operation curve can be compared with the historical second total operation curve to generate a target operation curve that can reflect the load change characteristics at the current moment. The target operation curve represents the change of the current total load compared with the previous moment, and can more clearly highlight the type characteristics of the newly connected load or the start-stop load, thereby improving the accuracy of load identification.

[0095] Step S10626: Use the target operating curve to match at least one load characteristic curve in the load characteristic curve library to obtain the power load type of the current power supply system.

[0096] In this embodiment, the load characteristic curve may be a set of curves used to describe the electrical characteristics of different types of loads in startup, operation, start-stop and different power states. These curves can reflect the dynamic change characteristics of various electrical data (for example, current, voltage, power, etc.) of the load over time, as well as the typical characteristics of the load when switching between different working states.

[0097] In this embodiment, the load characteristic curve can be a current-time characteristic curve (IT curve), a current-voltage characteristic curve (IU curve), a power-time characteristic curve (PT curve), an active power-reactive power characteristic curve (PQ curve), a phase angle-time characteristic curve, a start-stop number-time characteristic curve, a current-power change characteristic curve, and a power fluctuation characteristic curve, etc.

[0098] In this embodiment, a first total operation curve is generated according to the first operation data and the second operation data, and a target operation curve reflecting the current load change characteristics is generated based on a comprehensive analysis of the first total operation curve at the current moment and the second total operation curve at the previous moment, thereby achieving dynamic tracking and judgment of the load state and type. Compared with the method of relying solely on single-moment data or fixed characteristic parameters for identification, this embodiment uses the target operation curve to match the standard load characteristic curve in the load characteristic curve library, which can more accurately reflect the dynamic change characteristics and periodic laws of the load operation state, thereby significantly improving the recognition accuracy and robustness in complex load scenarios. At the same time, the method can adaptively respond to changes in load characteristics over time or usage scenarios, effectively avoid identification errors caused by load state switching or power fluctuations, ensure accurate distinction between different load types when multiple types of loads coexist, and improve the overall energy management efficiency and operation stability of the power supply system.

[0099] In some embodiments, the load characteristic curve includes a switch load characteristic curve and a flexible load characteristic curve, and the load characteristic curve library is configured with at least one switch load characteristic curve and at least one flexible load characteristic curve; the step of using the target operation curve to match at least one load characteristic curve in the load characteristic curve library to obtain the power load type of the current power supply system may include: Matching is performed using the target operation curve and at least one switching load characteristic curve and at least one flexible load characteristic curve in the load characteristic curve library.

[0100] When the similarity between the target operation curve and the flexible load characteristic curve meets the similarity threshold, it is concluded that there is at least one flexible power load in the current power supply system.

[0101] In this embodiment, the switch load characteristic curve may be a curve representing the change of electrical data (current, voltage, power) of the switch load over time in different states such as starting, running, and stopping. The switch load often has a clear start-stop characteristic, and exhibits obvious state switching when the switch is in action, such as instantaneous jumps in current and power, while its electrical characteristics usually remain stable during operation. The characteristic curve can intuitively reflect the start-stop behavior, start-up duration, and steady-state characteristics of the load.

[0102] Switching loads are loads that have only two clear states ("on" or "off") during operation, that is, they are either fully powered on (on) or completely powered off (off), with no continuous power regulation in between. Such loads will experience significant sudden changes in electrical parameters at startup, while power and current are usually maintained at fixed values ​​during steady-state operation. Typical switching loads include lighting equipment (such as ordinary light bulbs), traditional fixed-speed air conditioners, refrigerator compressors, and electric water heaters.

[0103] The switch load characteristic curve can be a current-time characteristic curve (IT curve), a power-time characteristic curve (PT curve), a starting current characteristic curve, etc.

[0104] The flexible load characteristic curve describes the continuous change characteristics of electrical data (power, current or voltage) of the flexible load over time in different working modes and power regulation states. Flexible loads can dynamically adjust power according to external power supply conditions, system status or regulation strategies, rather than having only two states of "on" and "off". This characteristic curve can reflect the gradual change characteristics of the load electrical parameters during power regulation, the change characteristics when the mode is switched, and the smooth transition characteristics between different power levels. Flexible loads are load types that can dynamically adjust their own power consumption or operating mode within a certain range according to system power supply conditions, load status or user needs. Flexible loads usually have multiple operating states (such as low power, medium power and high power), and can be flexibly adjusted according to system instructions or load strategies (such as reducing power, switching modes, enabling energy-saving modes, etc.). Typical flexible loads include variable frequency air conditioners, smart refrigerators, dimmable LED lamps and smart home appliances.

[0105] The flexible load characteristic curve may include a power-time characteristic curve (PT curve), a current-time characteristic curve (IT curve) and a multi-mode switching characteristic curve.

[0106] In this embodiment, by matching the target operation curve with the switch load characteristic curve and the flexible load characteristic curve in the load characteristic curve library, and judging the similarity between the target operation curve and the flexible load characteristic curve based on the matching result, when the similarity reaches the preset threshold, the flexible load type existing in the current power supply system can be accurately identified. This method can effectively distinguish between traditional switch-type loads (for example, ordinary lighting, fixed-speed air conditioners, etc.) and flexible loads that can be adjusted according to the system state (for example, variable-frequency air conditioners, smart home appliances, variable-frequency motors, etc.). Compared with the method based on single feature recognition, this embodiment can more accurately capture the dynamic characteristics of flexible loads in different power modes (such as power fluctuations or switching behaviors of flexible loads in different operating modes) by introducing a flexible load characteristic curve library and a similarity matching algorithm, thereby significantly improving the recognition accuracy and adaptability of the system to complex load environments. In addition, after the flexible load type is identified, the method can further support the system to perform intelligent energy allocation and power optimization according to the characteristic curve of the flexible load, thereby realizing efficient management and flexible regulation of the overall power supply system and improving the economy and stability of the power supply system.

[0107] In some implementations, when the operation mode is grid-connected operation, the method further includes: Step S108: sending a request to the electric meter device to obtain third operating data for characterizing the operating state of a second AC load; wherein the second AC load is an AC load powered by a power grid.

[0108] In this implementation, the second AC load may be represented as an AC load other than the first AC load.

[0109] Step S110: determining first operating data for characterizing an operating state of a DC load and second operating data for characterizing an operating state of a first AC load.

[0110] In this embodiment, the determined action may be the same as that in the above embodiment, and will not be described in detail here.

[0111] Step S112: Identify the first operating data, the second operating data and the third operating data using a preset power load identification strategy to obtain the power load type of the current power supply system.

[0112] In this embodiment, the preset power load identification strategy, the identification action and the power load type may be the same as those in the above embodiment, and will not be described in detail here.

[0113] In this implementation, by sending a request to the electric meter device in the grid-connected operation mode to obtain the third operation data of the second AC load, and combining the first operation data and the second operation data of the DC load and the first AC load in the power supply system for unified identification, comprehensive identification of all types of loads under multiple power supply modes can be achieved. Compared with the method of relying solely on local data for identification, this implementation can effectively distinguish different load types and their characteristics powered by photovoltaic power and grid power, and avoid load confusion and identification errors caused by multi-source power supply. At the same time, by integrating and analyzing the three types of operation data, it can more accurately reflect the actual working status of the load in the grid-connected mode, thereby improving the system's load identification capability and power supply strategy optimization capability in a complex power grid environment, ensuring accurate identification and energy management of various loads in the grid-connected mode, and providing reliable data support for the efficient operation and intelligent regulation of the system.

[0114] like Figure 4 As shown, this embodiment provides a flexible control method, which may include: Step S202: using the power load type identification method provided in the above-mentioned embodiment to identify at least one power load type of the current power supply system; wherein the power load type includes at least a flexible power load type.

[0115] Step S204: When there is at least one type of flexible power load, flexible control is performed on the power supply system and / or the load corresponding to the flexible power load based on a preset flexible control strategy.

[0116] In this embodiment, the preset flexible control strategy may include a power regulation strategy. For example, the power consumption level of the flexible load can be dynamically adjusted according to the current power supply conditions of the power supply system (such as photovoltaic power generation and energy storage battery power) to ensure that the power supply system operates in an efficient state. When the power supply is insufficient, the power of the flexible load is gradually adjusted from a high-power mode to a low-power mode, such as switching a variable-frequency air conditioner from a full-load mode to an energy-saving mode. When the power supply is sufficient, the power consumption of the flexible load is gradually increased so that it is switched to an efficient mode to make full use of renewable energy (such as enabling a flexible load in an efficient mode when the photovoltaic power generation is sufficient).

[0117] The preset flexible control strategy may also include a mode switching strategy. For example, by changing the working mode of the flexible load (for example, switching from the standard mode to the energy-saving mode), the load power can be dynamically adjusted to avoid the impact of insufficient power supply or excessive load on the stability of the system.

[0118] like Figure 8As shown, in a specific implementation scheme, the intelligent photovoltaic storage machine can adjust the power output size of the AC / DC conversion module by controlling PWM1-PWM4 to achieve a stable supply and bidirectional flow of AC power. The power conversion efficiency of the DC / DC conversion module can be adjusted by controlling PWM5-PWM8 to stabilize the DC output voltage. In this implementation, the flexible power load in the current power supply system is identified by using a power load type identification method, and based on the identification result, when the flexible power load is detected, a preset flexible control strategy is used to perform precise flexible control on the power supply system and / or the flexible power load, so as to achieve efficient management and dynamic adjustment of the flexible load in the power supply system. Different from the traditional fixed power control method, this implementation can flexibly adjust the working mode or power consumption level of the flexible load according to the actual operating state of the flexible load and the overall load of the system, thereby effectively reducing the load fluctuation and energy consumption during system operation. This method can not only intelligently reduce the power of flexible loads during periods of insufficient power supply or peak loads to ensure stable power supply for key loads, but also optimize energy use by reasonably allocating electricity during periods of sufficient power supply, further improve the utilization efficiency of photovoltaic and energy storage systems, achieve economical operation of the system and intelligent allocation of electricity, and provide strong guarantees for the overall stability and economy of the power supply system.

[0119] like Fig. 9 As shown, according to an embodiment of the present invention, a device for identifying a type of power load is provided, and the device may include: A first identification module, which is used to identify the operation mode of the current power supply system; wherein the power supply system is configured to be powered at least by photovoltaic power, and the operation mode includes at least an off-grid operation mode; A determination module, which is used to determine, when the operation mode is off-grid operation, first operation data for characterizing the operation state of a DC load and second operation data for characterizing the operation state of a first AC load; wherein the first AC load is an AC load indicated as being preferentially powered by the photovoltaic power supply; The second identification module is used to identify the first operating data and the second operating data through a preset power load identification strategy to obtain at least one power load type of the current power supply system.

[0120] According to an embodiment of the present invention, an electronic device is provided. Fig.10 The electronic device in this embodiment may include one or more of the following components: a processor, a network interface, a memory, a non-volatile memory, and one or more applications, wherein the one or more applications may be stored in the non-volatile memory and configured to be executed by one or more processors, and the one or more programs are configured to execute the method described in the aforementioned method embodiment.

[0121] According to an embodiment of the present invention, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a computer, the computer executes the method described in any of the above embodiments.

[0122] According to an embodiment of the present invention, a computer program product comprising instructions is also provided. When the instructions are executed by a computer, the computer executes the method described in any one of the above embodiments.

[0123] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0124] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments, and this embodiment will not be described in detail here.

[0125] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0126] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0127] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for identifying the type of power load, characterized in that: The method comprises: Identify the operating mode of the current power supply system; wherein the power supply system is configured to be powered at least by photovoltaics, and the operating mode includes at least an off-grid operating mode; When the operation mode is off-grid operation, determining first operation data for characterizing the operation state of a DC load and second operation data for characterizing the operation state of a first AC load; wherein the first AC load is an AC load indicated as being preferentially powered by the photovoltaic power supply; The first operating data and the second operating data are identified by using a preset power load identification strategy to obtain at least one power load type of the current power supply system.

2. The method according to claim 1, characterized in that The first operating data at least includes current data, voltage data and power data of the DC load, and the second operating data at least includes current data, voltage data and power data of the first AC load; the step of determining the first operating data for characterizing the operating state of the DC load and the second operating data for characterizing the operating state of the first AC load includes: Collecting current data and voltage data of the DC load and current data and voltage data of the first AC load; The power data of the DC load is calculated based on the current data and the voltage data of the DC load, and the power data of the first AC load is calculated based on the current data and the voltage data of the first AC load.

3. The method according to claim 2, characterized in that The step of collecting the current data and voltage data of the DC load includes: Collecting the current data of the DC load from a preset DC interface through a preset DC current sampling circuit; The voltage data of the DC load is collected from a preset DC interface through a preset DC voltage sampling circuit.

4. The method according to claim 2, characterized in that: The step of collecting current data and voltage data of the first AC load includes: Collecting current data of the first AC load from a preset AC interface through a preset AC current sampling circuit; The voltage data of the first AC load is collected from a preset AC interface through a preset AC voltage sampling circuit.

5. The method according to claim 1, characterized in that The preset power load identification strategy is a power load identification rule base, and the power load identification rule base is configured with at least one power load identification rule; the step of identifying the first operation data and the second operation data by the preset power load identification strategy to obtain the power load type of the current power supply system includes: The first operating data and the second operating data are identified based on at least one power load identification rule in the power load identification rule base to obtain a power load type of the current power supply system.

6. The method according to claim 5, characterized in that The power load identification rule base includes: a load characteristic curve base, wherein at least one load characteristic curve is configured in the load characteristic curve base; the step of performing identification on the first operation data and the second operation data based on the power load identification rule base to obtain the power load type of the current power supply system includes: Generate a first total operation curve according to the first operation data and the second operation data; wherein the first total operation curve is used to represent the total operation curve at the current moment; Generate a target operation curve based on the first total operation curve and a pre-stored second total operation curve; wherein the second total operation curve is a total operation curve before the first total operation curve; The target operation curve is matched with at least one load characteristic curve in the load characteristic curve library to obtain the power load type of the current power supply system.

7. The method according to claim 6, characterized in that The load characteristic curve includes a switch load characteristic curve and a flexible load characteristic curve, and the load characteristic curve library is configured with at least one switch load characteristic curve and at least one flexible load characteristic curve; the step of using the target operation curve to match at least one load characteristic curve in the load characteristic curve library to obtain the power load type of the current power supply system includes: Perform matching using the target operation curve and at least one switch load characteristic curve and at least one flexible load characteristic curve in the load characteristic curve library; When the similarity between the target operation curve and the flexible load characteristic curve meets the similarity threshold, it is concluded that there is at least one flexible power load in the current power supply system.

8. The method according to claim 1, characterized in that When the operation mode is grid-connected operation, the method further includes: Sending a request to the electric meter device to obtain third operating data for characterizing the operating state of a second AC load; wherein the second AC load is an AC load powered by a power grid; Determine first operating data for characterizing an operating state of a DC load and second operating data for characterizing an operating state of a first AC load; The first operating data, the second operating data and the third operating data are identified by using a preset power load identification strategy to obtain the power load type of the current power supply system.

9. A flexible control method, characterized in that: The method comprises: Using the method for identifying the power load type described in any one of claims 1 to 8, identifying at least one power load type of the current power supply system; wherein the power load type at least includes a type of flexible power load; When there is at least one type of flexible power load, flexible control is performed on the power supply system and / or the load corresponding to the flexible power load based on a preset flexible control strategy.

10. A device for identifying the type of electrical load, characterized in that: The device comprises: A first identification module, which is used to identify the operation mode of the current power supply system; wherein the power supply system is configured to be powered at least by photovoltaic power, and the operation mode includes at least an off-grid operation mode; A determination module, which is used to determine, when the operation mode is off-grid operation, first operation data for characterizing the operation state of a DC load and second operation data for characterizing the operation state of a first AC load; wherein the first AC load is an AC load indicated as being preferentially powered by the photovoltaic power supply; The second identification module is used to identify the first operating data and the second operating data through a preset power load identification strategy to obtain at least one power load type of the current power supply system.

11. An electronic device, characterized in that: include: a memory, and one or more processors communicatively coupled to the memory; Instructions executable by the one or more processors are stored in the memory. The instructions are executed by the one or more processors to enable the one or more processors to implement the method according to any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that: The readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 9 is implemented.

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