Intelligent monitoring management method of solar power generation device and related equipment

Abstract

The invention provides an intelligent monitoring management method of a solar power generation device and related equipment, and relates to the technical field of solar power generation. The method comprises the following steps: acquiring state information of a solar power generation device, wherein the state information comprises load voltage, battery current and output current of a photovoltaic panel; inputting the state information into a power detection model to obtain the output power of the solar power generation device; according to the output power of the solar power generation device, indicating the solar power generation device to enter a corresponding working mode; the working mode comprises a grid-connected working mode, an off-grid working mode and a direct-current working mode. According to the method, the power detection model is utilized, dynamic adjustment is carried out according to the state information obtained in real time, changes under different environment conditions can be effectively handled, therefore, fluctuation of power output is reduced, intelligent judgment is carried out according to the output power, the most suitable working mode is switched to, and reasonable utilization of energy is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of solar power generation, and in particular to an intelligent monitoring and management method for a solar power generation device and related equipment. Background Art

[0002] In the context of the current global energy structure transformation, solar energy as a renewable energy source has received widespread attention. With the development of solar power generation technology, solar power generation devices are increasingly used in residential, commercial and industrial fields. However, the output power of solar power generation devices is affected by many factors, such as light intensity, temperature and the status of system components, which lead to the volatility and uncertainty of the output power. Traditional solar power generation control methods often have difficulty in effectively responding to these dynamic changes, resulting in low power generation efficiency, insufficient stability, and the inability to flexibly switch working modes according to different operating environments. Summary of the invention

[0003] Based on this, the purpose of the present invention is to provide an intelligent monitoring and management method and related equipment for a solar power generation device, so as to realize intelligent control of the solar power generation device and optimize its operating efficiency and stability.

[0004] In a first aspect, the present invention provides an intelligent monitoring and management method for a solar power generation device, which is applied to a solar power generation device, wherein the solar power generation device includes a photovoltaic panel and a controller, wherein the photovoltaic panel is connected to a battery, an electrical load and a power grid through a cable, and the method includes:

[0005] Obtaining status information of the solar power generation device, including load voltage, battery current and output current of the photovoltaic panel;

[0006] Inputting the state information into the power detection model to obtain the output power of the solar power generation device;

[0007] According to the output power of the solar power generation device, the solar power generation device is instructed to enter a corresponding working mode; the working modes include a grid-connected working mode, an off-grid working mode and a DC working mode.

[0008] In one embodiment, the power detection model is obtained by the following method:

[0009] Construct an input layer that receives status information from the solar power generation device;

[0010] Constructing a fuzzy reasoning module, the fuzzy reasoning module corresponds to the input variable through the input layer one by one, the fuzzy reasoning module includes a first membership function of the input variable, and the first membership function is used to describe the membership relationship between the input variable and the fuzzy language value;

[0011] A rule base is constructed based on the fuzzy reasoning module. The rule base includes fuzzy rules. The fuzzy rules are used to define the fuzzy relationship of the output power of the solar power generation device under different input conditions.

[0012] Performing fuzzy reasoning based on the first membership function and the rule base to obtain a second membership function of the output power;

[0013] An output layer is constructed, in which the second membership function of the output power is converted based on a defuzzification method and a numerical value of the output power is output;

[0014] Based on the input layer, the fuzzy reasoning module, the rule base, the second membership function of the output power and the output layer, a power detection model is obtained.

[0015] In one embodiment, the first membership function of the input variable is obtained by the following method, including:

[0016] Set the center point of the first membership function as the upper and lower limits of the input variable;

[0017] The first membership function is divided into two parts, and the upper and lower limits corresponding to the input variables are obtained respectively;

[0018] The first membership function is sliced ​​in the horizontal direction, and the membership of the first membership function on the corresponding horizontal slice is calculated according to the input variable and the first membership function to obtain the first membership function of the input variable of the power detection model.

[0019] In one embodiment, according to the output power of the solar power generation device, instructing the solar power generation device to enter a corresponding working mode includes:

[0020] Construct Lyapunov function based on power detection model;

[0021] According to the Lyapunov function and LaSalle theorem, the parameter update rule of the control signal and the power detection model is obtained; the control signal is used to adjust the output power of the solar power generation device to obtain the first target power;

[0022] Instructing the solar power generation device to enter a corresponding working mode according to the first target power;

[0023] The control signal includes a first voltage for controlling the output current of the photovoltaic panel and a second voltage for controlling the battery current; and the parameter updating rule is used to adjust the power detection model parameters according to the state information.

[0024] In one embodiment, after obtaining the parameter update rules of the control signal and the power detection model according to the Lyapunov function and the LaSalle theorem, it includes:

[0025] Based on the power detection model, an approximate error is calculated, and the approximate error includes a photovoltaic panel current error and a battery current error. The photovoltaic panel current error includes a difference between an actual photovoltaic panel output current and a photovoltaic panel output current estimated by the power detection model. The battery current error includes a difference between an actual battery current and a battery current estimated by the power detection model.

[0026] A compensator is set according to the approximate error, wherein the compensator includes a photovoltaic panel current compensation value corresponding to the photovoltaic panel current error and a battery current compensation value corresponding to the battery current error;

[0027] The calculation formulas for the photovoltaic panel current compensation value and the battery current compensation value are as follows:

[0028]

[0029] Where E1 is the photovoltaic panel current error, E2 is the battery current error, y1 is the error between the photovoltaic panel output current estimated by the power detection model, y2 is the error between the battery current estimated by the power detection model, e1 is the tracking error of y1, e2 is the tracking error of y2, ∈ is a constant used to avoid the situation where the denominator is zero;

[0030] Calculating according to the compensator and the control signal to obtain a second target power;

[0031] Based on the second target power, the solar power generation device is instructed to enter a corresponding working mode.

[0032] In one embodiment, obtaining status information of a solar power generation device includes:

[0033] The output current of the photovoltaic panel in the solar power generation device is obtained by a current sensor;

[0034] Obtaining the load voltage in the solar power generation device according to the voltage sensor;

[0035] The battery current of the solar power generation device is obtained based on the current sensor.

[0036] In one embodiment, according to the output power of the solar power generation device, instructing the solar power generation device to enter a corresponding working mode includes:

[0037] Comparing the output power of the solar power generation device with a first threshold value, and when the output power of the solar power generation device is greater than or equal to the first threshold value, indicating that the solar power generation device enters a grid-connected working mode;

[0038] or, when the output power of the solar power generation device is less than a first threshold value and greater than or equal to a second threshold value, instructing the solar power generation device to enter an off-grid working mode;

[0039] Or, when the output power of the solar power generation device is less than the second threshold, the solar power generation device is instructed to enter a DC working mode.

[0040] In a second aspect, the present invention further provides an intelligent monitoring and management system for a solar power generation device, which is applied to a solar power generation device, wherein the solar power generation device includes a photovoltaic panel and a controller, and the solar power generation device is connected to a battery, an electrical load and a power grid through a cable, and the system includes:

[0041] A status information acquisition module is used to acquire status information of the solar power generation device, the status information including load voltage, battery current and output current of the photovoltaic panel;

[0042] A power output module, used to input the status information into the power detection model to obtain the output power of the solar power generation device;

[0043] The mode switching module is used to instruct the solar power generation device to enter a corresponding working mode according to the output power of the solar power generation device; the working modes include a grid-connected working mode, an off-grid working mode and a DC working mode.

[0044] In a third aspect, the present invention further provides a solar power generation device, including a photovoltaic panel and a controller, wherein the photovoltaic panel is connected to a battery, an electrical load and a power grid via a cable;

[0045] The controller is used to execute the steps of an intelligent monitoring and management method for a solar power generation device.

[0046] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a method for intelligent monitoring and management of a solar power generation device.

[0047] In the above technical solution, the power detection model is used to perform intelligent monitoring and management of the solar power generation device, which can effectively handle the dynamic changes of photovoltaic panels, batteries and loads, such as temperature changes, radiation changes and load mutations, etc., improve power generation efficiency and system stability, and can intelligently select the grid-connected working mode, off-grid working mode and DC working mode according to the output power of the solar power generation device to adapt to different operating environments and requirements, thereby improving system reliability.

[0048] For better understanding and implementation, the present invention is described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A flow chart of an intelligent monitoring and management method for a solar power generation device is provided in one embodiment of the present invention;

[0050] Figure 2A schematic diagram of a process for obtaining a power detection model in one embodiment of the present invention;

[0051] Figure 3 The figure is a schematic diagram of the structure of an intelligent monitoring and management system for a solar power generation device in one embodiment of the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0053] In one embodiment, Figure 1 As shown, a method for intelligent monitoring and management of a solar power generation device is provided. In this embodiment, the method is applied to a solar power generation device, and the solar power generation device includes a photovoltaic panel and a controller. The photovoltaic panel is connected to a battery, a power load and a power grid through a cable. The embodiment of the present application uses the method applied to the controller of a solar power generation device as an example. It can be understood that the controller can also be a control terminal or a control server connected to the solar power generation device, which is not limited here. Figure 1 As shown, the method comprises the following steps:

[0054] S101: Acquire status information of the solar power generation device, where the status information includes load voltage, battery current, and output current of the photovoltaic panel.

[0055] For example, the solar power generation device can be monitored in real time. The specific monitoring method depends on the specific application scenario and requirements, and then its status information can be obtained. The information includes the load voltage at both ends of the power load, the battery current and the output current of the photovoltaic panel.

[0056] S102: Input the state information into a power detection model to obtain the output power of the solar power generation device.

[0057] Specifically, the power detection model is a control model based on fuzzy control logic, which is used to deal with uncertainty and fuzziness. Inputting state information into the power detection model can effectively deal with the uncertainty and nonlinear factors in the information, and the output power of the solar power generation device can be obtained. According to the output power, corresponding control can be performed to improve the performance and efficiency of the system.

[0058] S103: According to the output power of the solar power generation device, instruct the solar power generation device to enter a corresponding working mode; the working modes include a grid-connected working mode, an off-grid working mode and a DC working mode.

[0059] Exemplarily, the grid-connected operation mode may refer to the normal grid-connected operation of the solar power generation device, at which time the device generates electricity to supply power to the load, the remaining energy is used to charge the battery, and the energy that cannot be consumed by the battery is fed back to the grid to sell electricity; the off-grid operation mode may refer to the off-grid operation of the solar power generation device, at which time the device and the battery are operated with load, if the power generation energy of the device is greater than the load power, the remaining energy is used to charge the battery, if it is less than the load, the battery needs to supplement the energy required by the load; the DC operation mode may refer to the solar power generation device no longer supplying power to the load, at which time the device generates electricity to the battery to charge the battery. By evaluating the output power of the solar power generation device, the solar power generation device can be controlled to enter the corresponding operation mode. This can be achieved by controlling devices such as inverters and switches to switch the operation mode. The operation mode can be divided into a grid-connected operation mode, an off-grid operation mode and a DC operation mode, which are automatically switched according to the output power. By selecting the appropriate operation mode, solar energy resources can be maximized, energy loss can be reduced, and efficiency and system reliability can be further improved.

[0060] The method obtains the status information of the solar power generation device, calculates the output power based on the power detection model, handles the uncertainty in the information, effectively adjusts the output power, improves the energy utilization efficiency, and controls the solar power generation device to switch to the corresponding working mode according to the output power, including grid-connected working mode, off-grid working mode and DC working mode, to ensure stable operation under different environmental conditions, thereby maximizing the use of solar energy, reducing energy loss and improving the overall system reliability.

[0061] Further, such as Figure 2 As shown, the power detection model is obtained by the following method:

[0062] S201: constructing an input layer, the input layer receiving status information from the solar power generation device;

[0063] S202: construct a fuzzy reasoning module, the fuzzy reasoning module corresponds to the input variable through the input layer one by one, the fuzzy reasoning module includes a first membership function of the input variable, and the first membership function is used to describe the membership relationship between the input variable and the fuzzy language value;

[0064] S203: constructing a rule base based on the fuzzy reasoning module, the rule base including fuzzy rules, and the fuzzy rules are used to define the fuzzy relationship of the output power of the solar power generation device under different input conditions;

[0065] S204: performing fuzzy reasoning according to the first membership function and the rule base to obtain a second membership function of the output power;

[0066] S205: Obtain a power detection model based on the input layer, the fuzzy reasoning module, the rule base, the second membership function of the output power and the output layer.

[0067] Specifically, the power detection model can be an improved three-stage fuzzy logic system, which is used to deal with uncertainty and ambiguity and is suitable for complex and dynamic environments, such as solar power generation devices. The power detection model can receive the state information of the solar power generation device through the input layer, and use the fuzzy reasoning module to assign the first membership function corresponding to the input variable. After building the rule base, the relationship between the input variable and the output power is modeled according to the rule base, and then fuzzy reasoning is performed to obtain the second membership function of the output power; the output power value is obtained by the defuzzification method in the output layer. Finally, based on the input layer, the fuzzy reasoning module, the rule base, the second membership function of the output power and the output layer, the power detection model is obtained.

[0068] Exemplarily, the acquired state information can be subjected to data preprocessing, such as selecting the same sampling time for normalization, denoising, etc., and then input into the power detection model. Since it takes a certain amount of time to measure and obtain the load voltage in the actual system, in order to compensate for the sampling delay, the load voltage can be delayed at the same sampling time and then input into the power detection model. The corresponding membership functions are used to represent the fuzzy sets of the input load voltage, battery current, and output current of the photovoltaic panel. The membership functions can be Gaussian, triangular, trapezoidal, and other shapes. Then calculate the membership value of each membership function, match it with the pre-defined rules in the rule base, and activate the rules that meet the conditions. Each rule contains a premise and a conclusion. The premise describes the conditions of the input variables, and the conclusion describes the output power of the output variables. The weight of the activated rule can be calculated by a variety of methods, such as the minimum method, the product method, and the like.

[0069] According to the first membership function and the rule base, fuzzy reasoning is performed, that is, for each activated rule, the membership value of the conclusion is calculated according to its weight and the membership value of the premise, and the conclusion of the activated rule is merged into a fuzzy set, that is, the second membership function of the output power, through the rule reasoning algorithm such as the maximum membership method, the centroid method, etc. Based on the defuzzification algorithm such as the centroid method, the maximum membership method, etc., the second membership function of the output power is expressed as a single precise value, and finally output by the output layer.

[0070] Furthermore, the first membership function of the input variable can be obtained by the following method, including:

[0071] S301: setting the center point of the first membership function as the upper limit and lower limit of the input variable;

[0072] S302: Divide the first membership function into two parts to obtain an upper limit and a lower limit corresponding to the input variable respectively;

[0073] S303: Slice the first membership function along the horizontal direction, and calculate the membership of the first membership function on the corresponding horizontal slice according to the input variable and the first membership function to obtain the first membership function of the input variable of the power detection model.

[0074] Specifically, for each input variable, such as the first membership function of the output current of the photovoltaic panel, two Gaussian membership functions are defined, and the center point of the membership function is set as the upper and lower limits of the variable, thereby dividing the membership function into two parts, corresponding to the upper and lower limits of the input variable, respectively, so that the membership relationship in different ranges can be more clearly represented. Each membership function is sliced ​​in the horizontal direction to obtain multiple horizontal slices, each horizontal slice representing a specific membership level. For each input variable and each horizontal slice, the membership of the membership function on the horizontal slice is calculated according to the value of the input variable and the membership function, and the first membership function of the input variable can be obtained. The first membership function is an interval membership function, whose center point corresponds to the value of the input variable, and whose width represents the degree of uncertainty.

[0075] Further, according to the output power of the solar power generation device, instructing the solar power generation device to enter a corresponding working mode includes:

[0076] S401: Constructing Lyapunov function based on power detection model;

[0077] S402: Obtaining a control signal and a parameter update rule of a power detection model according to a Lyapunov function and LaSalle theorem; the control signal is used to adjust the output power of the solar power generation device to obtain a first target power;

[0078] S404: instructing the solar power generation device to enter a corresponding working mode according to the first target power;

[0079] The control signal includes a first voltage for controlling the output current of the solar power generation device and a second voltage for the battery current; and the parameter updating rule is used to adjust the power detection model parameters according to the state information.

[0080] The Lyapunov function can help determine whether the system state tends to a stable state in a dynamic system. Based on the LaSalle theorem, by constructing the Lyapunov function, it can help design a controller to ensure that the system can remain stable when disturbed, thereby obtaining the control signal and the parameter update rule of the power detection model. The control signal is used to adjust the output power of the solar power generation device to achieve the set target power, that is, the first target power. According to the first target power, the solar power generation device can be instructed to switch to a suitable operating mode to optimize energy output. Specifically, the control signal can include adjusting the output current and battery current of the photovoltaic panel. The parameter update rule can enable the power detection model to adapt to changes in real-time status information, thereby enhancing the adaptability and performance of the control system by continuously adjusting its parameters.

[0081] Furthermore, after obtaining the parameter update rules of the control signal and the power detection model according to the Lyapunov function and LaSalle theorem, the following are included:

[0082] S501: Calculate an approximate error based on a power detection model, where the approximate error includes a photovoltaic panel current error and a battery current error. The photovoltaic panel current error includes a difference between an actual photovoltaic panel output current and an estimated photovoltaic panel output current by the power detection model. The battery current error includes a difference between an actual battery current and an estimated battery current by the power detection model.

[0083] S502: Setting a compensator according to the approximate error, the compensator including a photovoltaic panel current compensation value corresponding to the photovoltaic panel current error and a battery current compensation value corresponding to the battery current error;

[0084] The calculation formulas for the photovoltaic panel current compensation value and the battery current compensation value are as follows:

[0085]

[0086] Where E1 is the photovoltaic panel current error, E2 is the battery current error, y1 is the error between the photovoltaic panel output current estimated by the power detection model, y2 is the error between the battery current estimated by the power detection model, e1 is the tracking error of y1, e2 is the tracking error of y2, ∈ is a constant used to avoid the situation where the denominator is zero;

[0087] S503: Calculate according to the compensator and the control signal to obtain a second target power;

[0088] S504: Based on the second target power, instruct the solar power generation device to enter a corresponding working mode.

[0089] Exemplarily, the performance of the solar power generation device can be further optimized through a compensation mechanism. First, based on the power detection model, the approximate error can be calculated, including the photovoltaic panel current error and the battery current error. The photovoltaic panel current error is the difference between the actual output current and the model estimated value; the battery current error is the same. However, in the real world, due to the many nonlinear, uncertain and time-varying factors, it is difficult to establish an accurate mathematical model to describe the behavior of the system, that is, it is difficult to directly calculate the approximate error. Preferably, the approximate error can be obtained by calculating the upper bound of the approximate error, thereby ensuring the conservatism of the system stability analysis, simplifying the controller design process, and improving the robustness of the controller.

[0090] Based on the approximate error, a compensator is set to provide a compensation value for the approximate error. These compensation values ​​are intended to correct the output inconsistency caused by the error. The calculation formula of the compensation value takes into account the photovoltaic panel and battery current errors, and introduces a constant to avoid the situation where the denominator is zero during the calculation process. Combining the results of the compensator and the control signal, the second target power is calculated, which will be used by the system to instruct the solar power generation device to enter the corresponding working mode to ensure efficient and stable operation. Exemplarily, the compensator output can be combined with the control signal to obtain the second target power, usually by weighted or linear combination.

[0091] Furthermore, the status information of the solar power generation device is obtained, including:

[0092] The output current of the photovoltaic panel in the solar power generation device is obtained by a current sensor;

[0093] Obtaining the load voltage in the solar power generation device according to the voltage sensor;

[0094] The battery current of the solar power generation device is obtained based on the current sensor.

[0095] For example, a current sensor can be used to measure the current generated by a solar photovoltaic panel. This data helps to evaluate the performance of the photovoltaic panel and can also reflect its power generation capacity under specific conditions. At the same time, the load voltage represents the voltage received by the device or circuit connected to the solar power generation device. This important parameter can be effectively obtained through real-time monitoring of the voltage sensor. The battery current refers to the current of the battery during the charging and discharging process. The battery current can be monitored by a current sensor to determine the battery's charging status and its working efficiency. In summary, different types of sensors can be used to obtain the key electrical parameters of the solar power generation device according to different application scenarios and requirements, so as to achieve real-time monitoring and management of it and ensure the stability and performance optimization of the system.

[0096] Further, according to the output power of the solar power generation device, instructing the solar power generation device to enter a corresponding working mode includes:

[0097] Comparing the output power of the solar power generation device with a first threshold value, and when the output power of the solar power generation device is greater than or equal to the first threshold value, indicating that the solar power generation device enters a grid-connected working mode;

[0098] or, when the output power of the solar power generation device is less than a first threshold value and greater than or equal to a second threshold value, instructing the solar power generation device to enter an off-grid working mode;

[0099] Or, when the output power of the solar power generation device is less than the second threshold, the solar power generation device is instructed to enter a DC working mode.

[0100] Specifically, when the output power of the solar power generation device is greater than or equal to the first threshold, the device enters the grid-connected working mode. The grid-connected operating mode may refer to the normal grid-connected operation of the solar power generation device. At this time, the device generates electricity to supply power to the load, and the remaining energy is used to charge the battery. The energy that cannot be consumed by the battery is fed back to the grid to sell electricity, so as to achieve the energy flow function of self-generation and self-use, and the surplus power is connected to the grid, so as to maximize the power generation income. If the output power of the solar power generation device is between the first threshold and the second threshold, that is, less than the first threshold but greater than or equal to the second threshold, the device will switch to the off-grid working mode. The off-grid working mode may refer to the off-grid operation of the solar power generation device. In this case, the device cannot be effectively connected to the grid, which may be due to insufficient light, but it can still generate a certain amount of electricity to supply the local load. At this time, the device and the battery are operated with the load. If the power generation energy of the device is greater than the load power, the remaining energy is used to charge the battery. If it is less than the load, the battery needs to supplement the energy required by the load. When the output power of the solar power generation device is less than the second threshold, the device enters the DC working mode. This means that the power generation capacity of the device is low and may not be enough to support any external load. The generated DC power will be directly used for basic operation or storage. The device no longer supplies power to the load. At this time, the device generates electricity to the battery to charge the battery.

[0101] In one embodiment, Figure 3 As shown, the present invention also provides an intelligent monitoring and management system 300 for a solar power generation device, which is applied to a solar power generation device, wherein the solar power generation device includes a photovoltaic panel and a controller, and the solar power generation device is connected to a battery, an electrical load and a power grid through a cable, and the intelligent monitoring and management system includes:

[0102] The status information acquisition module 301 is used to acquire the status information of the solar power generation device, and the status information includes the load voltage, the battery current and the output current of the solar power generation device;

[0103] The power output module 302 is used to input the state information into the power detection model to obtain the output power of the solar power generation device;

[0104] The mode switching module 303 is used to instruct the solar power generation device to enter a corresponding working mode according to the output power of the solar power generation device; the working modes include a grid-connected working mode, an off-grid working mode and a DC working mode.

[0105] The system is constructed by constructing three modules. The status information acquisition module can monitor the solar power generation device in real time to obtain its real-time status information. The power output module inputs the status information into the power detection model to obtain the output power of the solar power generation device. The output power of the solar power generation device is compared and evaluated in the mode switching module, so that the solar power generation device can enter the corresponding working mode. Through this system, the status information of the solar power generation device can be obtained and analyzed in real time, so as to optimize the power output and working mode and improve the overall efficiency and stability of the system. Through intelligent decision-making, the system can automatically switch the working mode according to real-time data to ensure that the solar power generation device always operates in the best state under different load and environmental conditions, thereby improving energy utilization and extending the life of the equipment.

[0106] In one embodiment, the system further includes a model building module 304, which is used to obtain a power detection model by the following method, including:

[0107] Construct an input layer that receives status information from the solar power generation device;

[0108] Constructing a fuzzy reasoning module, the fuzzy reasoning module corresponds to the input variable through the input layer one by one, the fuzzy reasoning module includes a first membership function of the input variable, and the first membership function is used to describe the membership relationship between the input variable and the fuzzy language value;

[0109] A rule base is constructed based on the fuzzy reasoning module. The rule base includes fuzzy rules. The fuzzy rules are used to define the fuzzy relationship of the output power of the solar power generation device under different input conditions.

[0110] Performing fuzzy reasoning based on the first membership function and the rule base to obtain a second membership function of the output power;

[0111] An output layer is constructed, in which the second membership function of the output power is converted based on a defuzzification method and a numerical value of the output power is output;

[0112] Based on the input layer, the fuzzy reasoning module, the rule base, the second membership function of the output power and the output layer, a power detection model is obtained.

[0113] Furthermore, the model building module 304 is also used to obtain the first membership function of the input variable by the following method, including:

[0114] Set the center point of the first membership function as the upper and lower limits of the input variable;

[0115] The first membership function is divided into two parts, and the upper and lower limits corresponding to the input variables are obtained respectively;

[0116] The first membership function is sliced ​​in the horizontal direction, and the membership of the first membership function on the corresponding horizontal slice is calculated according to the input variable and the first membership function to obtain the first membership function of the input variable of the power detection model.

[0117] In one embodiment, based on the power detection model, the mode switching module 303 is also used to construct a Lyapunov function;

[0118] According to the Lyapunov function and LaSalle theorem, the parameter update rule of the control signal and the power detection model is obtained; the control signal is used to adjust the output power of the solar power generation device to obtain the first target power;

[0119] Instructing the solar power generation device to enter a corresponding working mode according to the first target power;

[0120] The control signal includes a first voltage for controlling the output current of the photovoltaic panel and a second voltage for controlling the battery current; and the parameter updating rule is used to adjust the power detection model parameters according to the state information.

[0121] Further, after obtaining the parameter update rules of the control signal and the power detection model according to the Lyapunov function and the LaSalle theorem, the mode switching module 303 is also used to calculate the approximate error based on the power detection model, and the approximate error includes the photovoltaic panel current error and the battery current error. The photovoltaic panel current error includes the difference between the actual output current of the photovoltaic panel and the photovoltaic panel output current estimated by the power detection model, and the battery current error includes the difference between the actual battery current and the battery current estimated by the power detection model.

[0122] A compensator is set according to the approximate error, wherein the compensator includes a photovoltaic panel current compensation value corresponding to the photovoltaic panel current error and a battery current compensation value corresponding to the battery current error;

[0123] The calculation formulas for the photovoltaic panel current compensation value and the battery current compensation value are as follows:

[0124]

[0125] Among them, E1 is the PV panel current error, E2 is the battery current error, y1 is the error between the PV panel output current estimated by the power detection model, y2 is the error between the battery current estimated by the power detection model, e1 is the tracking error of y1, e2 is the tracking error of y2, and ∈ is a constant used to avoid the situation where the denominator is zero.

[0126] Calculating according to the compensator and the control signal to obtain a second target power;

[0127] Based on the second target power, the solar power generation device is instructed to enter a corresponding working mode.

[0128] In one embodiment, the status information acquisition module 301 is also used to obtain the output current of the photovoltaic panel in the solar power generation device through a current sensor; obtain the load voltage in the solar power generation device according to a voltage sensor; and obtain the battery current of the solar power generation device based on the current sensor.

[0129] In one embodiment, the mode switching module 303 is further used to compare the output power of the solar power generation device with a first threshold value, and when the output power of the solar power generation device is greater than or equal to the first threshold value, instruct the solar power generation device to enter the grid-connected working mode;

[0130] or, when the output power of the solar power generation device is less than a first threshold value and greater than or equal to a second threshold value, instructing the solar power generation device to enter the off-grid working mode;

[0131] Or, when the output power of the solar power generation device is less than a second threshold, the solar power generation device is instructed to enter the DC working mode.

[0132] In one embodiment, the present invention further provides a solar power generation device, including a photovoltaic panel and a controller, wherein the photovoltaic panel is connected to a battery, a power load and a power grid through a cable; the controller is used to execute the steps of an intelligent monitoring and management method for a solar power generation device. Specifically, the method may include steps such as obtaining status information, information input, power output, and mode switching of the solar power generation device, so that the solar power generation device can automatically adjust its working state under different load and environmental conditions through intelligent monitoring and management, thereby achieving optimal energy utilization and equipment protection, and improving the economic benefits and reliability of the overall system.

[0133] In one embodiment, the present invention further provides a computer readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of a method for intelligent monitoring and management of a solar power generation device are implemented. The computer storage medium may include a random access memory, a read-only memory, a flash memory or other solid-state storage technology, a digital versatile disc or other optical storage, a cassette, a magnetic tape, a disk storage or other magnetic storage device.

[0134] The above-mentioned embodiments only express several implementation methods of the present invention, and the description is relatively specific and detailed, but it cannot be understood as limiting the scope of the invention patent. It should be pointed out that for ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention.

Claims

1. An intelligent monitoring and management method for a solar power generation device, characterized in that: Applied to a solar power generation device, the solar power generation device includes a photovoltaic panel and a controller, the photovoltaic panel is connected to a battery, an electrical load and a power grid through a cable, and the method includes: Acquiring status information of the solar power generation device, the status information including load voltage, battery current and output current of the photovoltaic panel; Inputting the state information into a power detection model to obtain the output power of the solar power generation device; According to the output power of the solar power generation device, the solar power generation device is instructed to enter a corresponding working mode; the working mode includes a grid-connected working mode, an off-grid working mode and a DC working mode.

2. The intelligent monitoring and management method for a solar power generation device according to claim 1, characterized in that: The power detection model is obtained by the following method: constructing an input layer, wherein the input layer receives the status information from the solar power generation device; Constructing a fuzzy reasoning module, wherein the fuzzy reasoning module corresponds one-to-one to the input variables passing through the input layer, and the fuzzy reasoning module includes a first membership function of the input variable, wherein the first membership function is used to describe the membership relationship between the input variable and the fuzzy language value; Building a rule base based on the fuzzy reasoning module, the rule base includes fuzzy rules, and the fuzzy rules are used to define the fuzzy relationship of the output power of the solar power generation device under different input conditions; Performing fuzzy reasoning according to the first membership function and the rule base to obtain a second membership function of output power; Constructing an output layer, in which the second membership function of the output power is converted based on a defuzzification method and a numerical value of the output power is output; The power detection model is obtained based on the input layer, the fuzzy reasoning module, the rule base, the second membership function of the output power and the output layer.

3. The intelligent monitoring and management method for a solar power generation device as claimed in claim 2, characterized in that: The first membership function of the input variable is obtained by the following method, including: Setting the center point of the first membership function as the upper limit and lower limit of the input variable; Dividing the first membership function into two parts to obtain an upper limit and a lower limit corresponding to the input variable respectively; The first membership function is sliced ​​in the horizontal direction, and the membership of the first membership function on the corresponding horizontal slice is calculated according to the input variable and the first membership function to obtain the first membership function of the input variable of the power detection model.

4. The intelligent monitoring and management method for a solar power generation device according to claim 1, characterized in that: The step of instructing the solar power generation device to enter a corresponding working mode according to the output power of the solar power generation device comprises: Constructing a Lyapunov function based on the power detection model; According to the Lyapunov function and LaSalle theorem, a control signal and a parameter update rule of the power detection model are obtained; the control signal is used to adjust the output power of the solar power generation device to obtain a first target power; Instructing the solar power generation device to enter a corresponding working mode according to the first target power; The control signal includes a first voltage for controlling the output current of the photovoltaic panel and a second voltage for controlling the battery current; and the parameter updating rule is used to adjust the power detection model parameters according to the state information.

5. The intelligent monitoring and management method for a solar power generation device as claimed in claim 4, characterized in that: After obtaining the control signal and the parameter update rule of the power detection model according to the Lyapunov function and the LaSalle theorem, it includes: Based on the power detection model, an approximate error is calculated, wherein the approximate error includes a photovoltaic panel current error and a battery current error, wherein the photovoltaic panel current error includes a difference between an actual photovoltaic panel output current and an estimated photovoltaic panel output current by the power detection model, and the battery current error includes a difference between an actual battery current and an estimated battery current by the power detection model; Setting a compensator according to the approximate error, the compensator comprising a photovoltaic panel current compensation value corresponding to the photovoltaic panel current error and a battery current compensation value corresponding to the battery current error; The calculation formulas for the photovoltaic panel current compensation value and the battery current compensation value are as follows: Wherein, E1 is the photovoltaic panel current error, E2 is the battery current error, y1 is the photovoltaic panel output current estimated by the power detection model, y2 is the error between the battery current estimated by the power detection model, e1 is the tracking error of y1, e2 is the tracking error of y2, ∈ is a constant used to avoid the situation where the denominator is zero; Performing calculation according to the compensator and the control signal to obtain a second target power; Based on the second target power, the solar power generation device is instructed to enter a corresponding working mode.

6. The intelligent monitoring and management method for a solar power generation device according to claim 1, characterized in that: The obtaining of status information of the solar power generation device comprises: Acquiring the output current of the photovoltaic panel in the solar power generation device through a current sensor; Acquiring the load voltage in the solar power generation device according to the voltage sensor; The battery current of the solar power generation device is obtained based on a current sensor.

7. The intelligent monitoring and management method for a solar power generation device according to claim 1, characterized in that: The step of instructing the solar power generation device to enter a corresponding working mode according to the output power of the solar power generation device comprises: Comparing the output power of the solar power generation device with a first threshold value, and when the output power of the solar power generation device is greater than or equal to the first threshold value, instructing the solar power generation device to enter the grid-connected working mode; or, when the output power of the solar power generation device is less than a first threshold value and greater than or equal to a second threshold value, instructing the solar power generation device to enter the off-grid working mode; Or, when the output power of the solar power generation device is less than a second threshold, the solar power generation device is instructed to enter the DC working mode.

8. An intelligent monitoring and management system for a solar power generation device, applied to the solar power generation device, the solar power generation device comprises a photovoltaic panel and a controller, the solar power generation device is connected to a battery, an electrical load and a power grid via a cable, and is characterized in that: The intelligent monitoring and management system comprises: A status information acquisition module, used for acquiring status information of the solar power generation device, wherein the status information includes load voltage, battery current and output current of the photovoltaic panel; A power output module, used for inputting the state information into the power detection model to obtain the output power of the solar power generation device; The mode switching module is used to instruct the solar power generation device to enter a corresponding working mode according to the output power of the solar power generation device; the working mode includes a grid-connected working mode, an off-grid working mode and a DC working mode.

9. A solar power generation device, characterized in that: It includes a photovoltaic panel and a controller, wherein the photovoltaic panel is connected to a battery, an electrical load and a power grid through a cable; The controller is configured to execute the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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