An intelligent control method for a photovoltaic power generation system

Abstract

The present invention relates to the technical field of intelligent regulation of photovoltaic power generation systems, and specifically discloses an intelligent regulation method for a photovoltaic power generation system. The method includes: collecting photovoltaic module information, confirming the output power at the maximum power point, judging the operating point of the photovoltaic module, and adjusting the output voltage perturbation step size. By deeply analyzing the influence of the surface dirt condition and aging condition of the photovoltaic module on the output power corresponding to the theoretically maximum power point, the present invention provides an effective data support basis for subsequent maximum power point tracking, and tracks the maximum power point according to the change rate of the actual output electric power of the photovoltaic module, and dynamically adjusts the size of the output voltage perturbation step size in real time, overcoming the problems of slow tracking speed and easy misjudgment in the traditional perturbation observation method and conductance increment method when the light intensity changes rapidly, enabling the photovoltaic module to work at the maximum power point in a timely and accurate manner, thereby improving the power generation efficiency of the photovoltaic module.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent regulation of photovoltaic power generation systems, and more specifically, to an intelligent regulation method for a photovoltaic power generation system. Background Art

[0002] Maximum power point tracking (MPPT) is a key technology in photovoltaic power generation systems. Its purpose is to enable photovoltaic modules to always operate near the maximum power point under different light intensity and temperature conditions, thereby maximizing the power generation efficiency of photovoltaic modules and the overall performance of photovoltaic power generation systems. Traditional perturbation observation method and conductance increment method have some limitations in practical applications. To overcome these limitations, intelligent variable step size MPPT algorithms have emerged.

[0003] For example, the patent with the Chinese patent publication number CN102811000B discloses a maximum power point tracking method and tracking device for a photovoltaic power generation system. The present invention uses the traversal method to quickly perform global optimization to find the quasi-maximum power point and the quasi-optimal duty cycle. Then, the perturbation observation method is used to dynamically track the voltage value in a small range near the quasi-optimal duty cycle with a small step size, and then track the maximum power point. The photovoltaic power generation system of the present invention has a fast response speed to solar tracking, a simple structure, does not require high-current and high-voltage sensors, has a low cost, and is also more reliable, safe and effective in operation.

[0004] For example, the patent with the Chinese patent publication number CN118740031A discloses a photovoltaic power generation MPPT control system based on the fixed voltage method and the conductance increment method, including: a photovoltaic cell array module, an MPPT control module, a fixed voltage controller, a conductance increment controller, an improved fixed voltage and conductance increment combination module, and a simulation test module. By combining the fixed voltage method and the conductance increment method, it realizes fast and efficient maximum power point tracking of the photovoltaic system. The fixed voltage method quickly approaches the maximum power point, and the conductance increment method accurately tracks. This method can quickly respond to environmental changes, reduce energy loss, improve dynamic response and control accuracy, and optimize parameters through simulation tests to ensure the efficient operation of the system under various conditions, improve energy conversion efficiency and system reliability.

[0005] There are also the following problems in the prior art: 1. The output power corresponding to the theoretically maximum power point of the current photovoltaic system is directly extracted without deeply analyzing the influence of the surface dirt condition and aging condition of the photovoltaic module on the output power corresponding to the theoretically maximum power point, which reduces the accuracy of confirming the output power corresponding to the theoretically maximum power point, and cannot provide an effective data support basis for the subsequent maximum power point tracking of the photovoltaic module, reducing the rationality of the maximum power point tracking, and thus reducing the regulation effect of the photovoltaic power generation efficiency.

[0006] 2. Currently, the maximum power point is tracked according to the environmental change situation, but not according to the change rate of the actual output electric power of the photovoltaic module. It cannot overcome the problems of slow tracking speed and easy misjudgment when the light intensity changes rapidly in the traditional perturbation observation method and conductance increment method, and cannot make the photovoltaic module work at the maximum power point in a timely and accurate manner, thus reducing the power generation efficiency of the photovoltaic module. Summary of the Invention

[0007] In view of this, to solve the problems raised in the above background technology, a smart control method for a photovoltaic power generation system is proposed.

[0008] The object of the present invention can be achieved through the following technical solutions: The present invention provides a smart control method for a photovoltaic power generation system, including the following steps: S1. Photovoltaic module information collection: Collect the surface light intensity and surface temperature of the photovoltaic modules in the target photovoltaic power generation park corresponding to each monitoring time period, and at the same time collect the surface images of the photovoltaic modules, and extract the service life, historical repair times and time points of each repair of the photovoltaic modules.

[0009] S2. Confirmation of the output power at the maximum power point: Extract the characteristic curves corresponding to the photovoltaic modules in the target photovoltaic power generation park, and confirm the output power corresponding to the theoretically maximum power point of the photovoltaic modules in each monitoring time period.

[0010] S3. Judgment of the operating point of the photovoltaic module: Extract the output voltage and output current corresponding to each monitoring time point in each monitoring time period of the photovoltaic module, and judge whether the operation of the photovoltaic module in each monitoring time period is at the maximum power point. If not, execute step S4. If so, it means that there is no need to perform step size regulation based on the change rate of the actual output power in the intelligent variable step size MPPT algorithm.

[0011] S4. Adjustment of the output voltage perturbation step size: Denote the monitoring time period in which the operation is not at the maximum power point as the time period to be regulated, extract the initial output voltage perturbation step size of each time period to be regulated, and start the step size regulation process based on the change rate of the actual output power in the intelligent variable step size MPPT algorithm.

[0012] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention deeply analyzes the influence of the surface dirt condition and aging condition of the photovoltaic module on the output power corresponding to the theoretically maximum power point, improves the accuracy of confirming the output power corresponding to the theoretically maximum power point, provides an effective data support basis for the subsequent maximum power point tracking of the photovoltaic module, and at the same time improves the rationality of the maximum power point tracking, thereby improving the regulation effect of the photovoltaic power generation efficiency.

[0013] (2) The present invention tracks the maximum power point according to the change rate of the actual output electric power of the photovoltaic module, and adjusts the size of the output voltage perturbation step in real time dynamically, overcoming the problems of slow tracking speed and easy misjudgment of the traditional perturbation observation method and conductance increment method when the light intensity changes rapidly, enabling the photovoltaic module to work at the maximum power point in a timely and accurate manner, thereby improving the power generation efficiency of the photovoltaic module. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for describing the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0015] Figure 1 It is a schematic flow chart of the method steps of the present invention.

[0016] Figure 2 It is a flowchart for judging whether the operation of the photovoltaic module of the present invention is at the maximum power point.

[0017] Figure 3 It is a flowchart for regulating the step size based on the change rate of the actual output power in the intelligent variable step size MPPT algorithm of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0019] Please refer to Figure 1 As shown, the present invention provides an intelligent regulation method for a photovoltaic power generation system, including: S1. Acquisition of photovoltaic module information: Acquire the surface light intensity and surface temperature of the photovoltaic modules in the target photovoltaic power generation park corresponding to each monitoring time period, and at the same time acquire the surface images of the photovoltaic modules, and extract the service life, historical repair times and time points of each repair of the photovoltaic modules.

[0020] It should be noted that the acquisition methods of the surface light intensity and surface temperature are as follows: Each light intensity sensor is arranged equidistantly on the surface of the photovoltaic module, and the light intensities collected by each light intensity sensor are averaged to obtain the surface light intensity. Each temperature sensor is arranged equidistantly on the surface of the photovoltaic module, and the temperatures collected by each temperature sensor are averaged to obtain the surface temperature.

[0021] It should also be noted that the surface image of the photovoltaic module is collected by a placed high-definition camera, and the service life, the number of historical repairs, and the time points of each repair of the photovoltaic module are all extracted from the photovoltaic module operation and maintenance management system in the target photovoltaic power generation park.

[0022] S2. Confirmation of the output power at the maximum power point: Extract the characteristic curve corresponding to the photovoltaic module in the target photovoltaic power generation park, and confirm the output power corresponding to the theoretically maximum power point of the photovoltaic module in each monitoring time period.

[0023] It should be noted that each type of photovoltaic module has its specific current-voltage characteristic curve and power-voltage characteristic curve. These characteristic curves describe the relationships among the output current, output voltage, and output power of the photovoltaic module under different light intensity and temperature conditions. The data of these characteristic curves can be obtained by referring to the product manual of the photovoltaic module or testing the photovoltaic module under laboratory conditions. In actual applications, according to the real-time collected light intensity and temperature data, through mathematical methods such as interpolation or fitting, the corresponding theoretical output current, output voltage, and output power can be found on the characteristic curve of the photovoltaic module, so as to determine the theoretically maximum power point of the photovoltaic module under the current environmental conditions.

[0024] In a specific embodiment of the present invention, the specific process of confirming the output power corresponding to the theoretically maximum power point of the photovoltaic module in each monitoring time period is as follows: A1. Substitute the surface light intensity and surface temperature corresponding to the photovoltaic module in each monitoring time period into the characteristic curve corresponding to the photovoltaic module in the target photovoltaic power generation park to find the uncorrected output power corresponding to the theoretically maximum power point.

[0025] A2. Perform fusion calculation based on the surface image, service life, number of historical repairs, and time points of each repair of the photovoltaic module to obtain the influence factor of the output power corresponding to the theoretically maximum power point of the photovoltaic module, and multiply it by the output power loss amount corresponding to the unit influence factor stored in the database to obtain the output power loss amount.

[0026] In a specific embodiment of the present invention, the specific process of calculating the influence factor of the output power corresponding to the theoretically maximum power point of the photovoltaic module is as follows: B1. Perform coupling processing on the number of surface dirt areas located in the surface image of the photovoltaic module and the dirt area of each dirt area to obtain the surface dirt degree of the photovoltaic module, and perform aging degree analysis on the service life, number of historical repairs, and time points of each repair of the photovoltaic module to obtain the aging degree of the photovoltaic module.

[0027] It should be noted that the acquisition methods for the number of surface dirt areas and the dirt area of each dirt area of the photovoltaic module are as follows: 1) Image acquisition: The surface image of the photovoltaic module is acquired through a high-definition camera. 2) Image preprocessing: First, the image is grayscale processed to convert the color image into a grayscale image. 3) Dirt area segmentation and recognition: By analyzing the grayscale difference between the surface dirt and the clean area of the photovoltaic module, a suitable threshold is selected for segmentation. The adaptive threshold segmentation method can be used to automatically determine the threshold according to the grayscale characteristics of the local area of the image. After segmentation, the dirt area and the background area are separated, facilitating subsequent counting and area measurement. 4) Counting the number of dirt areas and measuring the area: For the dirt areas after segmentation and processing, the number of dirt areas is counted through a marking algorithm. For the area measurement of each dirt area, it can be calculated by counting the number of pixels within the dirt area. In summary, the number of surface dirt areas and the dirt area of each dirt area of the photovoltaic module are obtained.

[0028] It should be noted that the specific process for obtaining the surface dirt degree of the photovoltaic module is as follows: The dirt areas of each dirt area of the photovoltaic module are accumulated to obtain the total dirt area of the photovoltaic module.

[0029] The differences between the number of surface dirt areas and the total dirt area of the photovoltaic module and the corresponding preset reference number of surface dirt areas and total dirt area are obtained. Then, the ratios are taken with the corresponding preset reference number of surface dirt areas and total dirt area respectively and accumulated to obtain the surface dirt degree of the photovoltaic module.

[0030] It should also be noted that relevant photovoltaic industry standards, specifications, or technical guides will give some reference indicators or recommended values for the surface dirt degree of photovoltaic modules. For example, the "Photovoltaic Power Station Component Cleaning Management Standard" document clearly stipulates the specific number of dirt areas and area. Based on this document standard, the preset reference number of surface dirt areas in the present invention is specifically 13 per square meter, and the preset reference total dirt area is specifically 9% of the total area of the photovoltaic module.

[0031] In a specific embodiment of the present invention, the specific process for obtaining the aging degree of the photovoltaic module is as follows: C1. The time points of each repair of the photovoltaic module are compared adjacent to each other to obtain the interval duration corresponding to each repair of the photovoltaic module, and the minimum value is extracted as the repair interval duration of the photovoltaic module.

[0032] C2. The repair interval duration, the historical repair times, and the service life of the photovoltaic module are respectively subjected to dynamic difference calculation with the corresponding preset reference values, and the normalized processing is performed on each dynamic difference and then accumulated to obtain the aging degree of the photovoltaic module.

[0033] It should be noted that the specific dynamic difference calculation is as follows: Subtract the preset reference maintenance interval duration from the maintenance interval duration to obtain the maintenance interval duration difference; subtract the historical maintenance times from the preset reference maintenance times to obtain the maintenance times difference; subtract the service life from the preset reference service life to obtain the service life difference. The specific normalization process is as follows: Divide the maintenance interval duration difference by the preset reference maintenance interval duration to obtain the normalized maintenance interval duration; divide the historical maintenance times by the preset reference maintenance times to obtain the normalized maintenance times; divide the service life difference by the preset reference service life to obtain the normalized service life.

[0034] It should also be noted that when analyzing the aging degree of photovoltaic modules, the service life directly reflects the duration of the photovoltaic modules experiencing environmental erosion and self-aging, and is a basic aging indicator; the maintenance interval duration can reflect the performance stability of the photovoltaic modules. A short interval indicates a rapid decline in performance and accelerated aging; while the maintenance times directly show the frequency of failures of the photovoltaic modules. A large number of times means frequent internal problems of the photovoltaic modules and serious aging conditions. By comprehensively analyzing these three parameters, the aging degree of the photovoltaic modules can be evaluated comprehensively and accurately, providing a strong basis for operation and maintenance decisions. Based on the importance of these parameters in the aging degree evaluation of photovoltaic modules, in the present invention, the preset reference maintenance interval duration is specifically 2 months, the preset reference historical maintenance times is specifically 4 times per year, the preset reference service life is 8 years, and the preset reference maintenance frequency is 2 times per year.

[0035] B2. Calculate the influence factor of the output power corresponding to the theoretical maximum power point of the photovoltaic module by fusing the surface dirtiness degree and the aging degree of the photovoltaic module.

[0036] It should be noted that the formula for calculating the influence factor of the output power corresponding to the theoretical maximum power point of the photovoltaic module by fusion calculation is: , where represents the influence factor of the output power, and respectively represent the surface dirtiness degree and the aging degree, and respectively represent the evaluation proportion weights of the influence factors of the output power corresponding to the set permitted surface dirtiness degree and aging degree, , represents the natural constant, is an adjustment parameter to control the growth rate of the influence factor.

[0037] It should also be noted that the value is obtained by fitting experimental data. The specific obtaining process is as follows: The first step is data collection: Obtain the measured values of the influence factors of the output power corresponding to different surface dirtiness degrees and aging degrees through experiments , the second-step fitting calculation: Using the formula as the model, and using fitting algorithms such as the least squares method, with minimized as the goal, the optimal value is inversely deduced.

[0038] It should also be noted that the design significance of the above formula is that the characteristics of the exponential function make naturally fall within the interval [0, 1]: when , , as increases, approaches 0, approaches 1, which fully meets the requirement that "the influence factor is between 0 and 1 and increases with the increase of the fouling degree and aging degree".

[0039] In a specific embodiment of the present invention, is set to 0.5, is set to 0.5. The evaluation proportion of the influence of the surface fouling degree and aging degree on the output power of the photovoltaic module is equally important, and various factors such as the use environment, service life, maintenance strategy and cost of the photovoltaic module need to be comprehensively considered and weighed.

[0040] A3. Subtract the uncorrected output power corresponding to the theoretically maximum power point of the photovoltaic module in each monitoring time period from the output power loss amount to obtain the output power corresponding to the theoretically maximum power point of the photovoltaic module in each monitoring time period.

[0041] Through in-depth analysis of the influence of the surface fouling situation and aging situation of the photovoltaic module on the output power corresponding to the theoretically maximum power point, the embodiment of the present invention improves the accuracy of confirming the output power corresponding to the theoretically maximum power point, provides an effective data support basis for the subsequent maximum power point tracking of the photovoltaic module, improves the rationality of the maximum power point tracking, and thus improves the regulation effect of the photovoltaic power generation efficiency.

[0042] S3. Photovoltaic module operating point judgment: Extract the output voltage and output current corresponding to each monitoring time point in each monitoring time period of the photovoltaic module, and judge whether the operation of the photovoltaic module in each monitoring time period is at the maximum power point. If not, perform step S4. If so, it indicates that there is no need to perform step size regulation based on the actual output power change rate in the intelligent variable step size MPPT algorithm.

[0043] It should be noted that the output voltage and output current corresponding to each monitoring time point in each monitoring time period of the photovoltaic module are extracted from the installed watt-hour meter.

[0044] In a specific embodiment of the present invention, the specific process of determining whether the operation of the photovoltaic module in each monitoring time period is at the maximum power point is as follows: D1. Multiply the output voltage and output current corresponding to each monitoring time point in each monitoring time period of the photovoltaic module to obtain the actual output power corresponding to each monitoring time point in each monitoring time period of the photovoltaic module, and perform an average calculation on it to obtain the actual output power corresponding to each monitoring time period of the photovoltaic module.

[0045] Please refer to Figure 2 As shown, D2. Compare the actual output power corresponding to each monitoring time period of the photovoltaic module with the output power corresponding to the theoretically maximum power point in each monitoring time period of the photovoltaic module. If the actual output power corresponding to a certain monitoring time period of the photovoltaic module is greater than or equal to the output power corresponding to the theoretically maximum power point in this monitoring time period, it indicates that the operation of the photovoltaic module in this monitoring time period is at the maximum power point; otherwise, it indicates that the operation of the photovoltaic module in this monitoring time period is not at the maximum power point.

[0046] S4. Output voltage perturbation step size adjustment: Denote the monitoring time periods in which the operation is not at the maximum power point as the time periods to be regulated, extract the initial output voltage perturbation step sizes of each time period to be regulated, and start the step size regulation process based on the actual output power change rate in the intelligent variable step size MPPT algorithm.

[0047] It should be noted that the magnitude of the output voltage is the perturbation step size of the output voltage.

[0048] It should be noted that the initial output voltage perturbation step sizes of each time period to be regulated are extracted from the maximum power point tracking (MPPT) control system.

[0049] Please refer to Figure 3 As shown, in a specific embodiment of the present invention, the process of starting the step size regulation process based on the actual output power change rate in the intelligent variable step size MPPT algorithm is as follows: E1. Extract the actual output power corresponding to each monitoring time point in each time period to be regulated of the photovoltaic module, and calculate the actual output power change rate of the photovoltaic module in each time period to be regulated.

[0050] In a specific embodiment of the present invention, the specific process of calculating the actual output power change rate of the photovoltaic module in each time period to be regulated is as follows: F1. Obtain the relative change rate of the actual output power corresponding to adjacent monitoring time points in each time period to be regulated of the photovoltaic module.

[0051] It should be noted that the formula for obtaining the relative change rate of the actual output power corresponding to adjacent monitoring time points in each time period to be regulated of the photovoltaic module is: , where represents the photovoltaic module at the The actual output power corresponding to the th monitoring time point in the th regulation period to be regulated, The actual output power corresponding to the th monitoring time point in the th regulation period to be regulated, , is the number of regulation periods to be regulated, represents the number of the monitoring time point, , is the number of monitoring time points.

[0052] F2. Sum the relative change rates of the actual output powers corresponding to all adjacent monitoring time points, and then divide by the number of monitoring time point intervals to obtain the actual output power change rate of the photovoltaic module in each regulation period to be regulated.

[0053] E2. When the actual output power change rate of the photovoltaic module in a certain regulation period to be regulated is greater than 0, mark this regulation period as a power increase period, and adjust the output voltage perturbation step length for each power increase period.

[0054] In a specific embodiment of the present invention, the specific process of adjusting the output voltage perturbation step length for each power increase period is as follows: when the actual output power of the photovoltaic module increases as the monitoring time point progresses, it indicates that the current perturbation direction of the output voltage of the photovoltaic module is correct, and the operating point is moving towards the maximum power point. In order to accelerate the speed of the operating point moving towards the maximum power point, adjust the output voltage perturbation step length according to the actual output power change rate and the initial output voltage perturbation step length in the power increase period to obtain the adjusted output voltage perturbation step length for each power increase period.

[0055] It should be noted that the specific formula for obtaining the adjusted output voltage perturbation step length for each power increase period is: , where represents the number of the power increase period, , is the number of power increase periods, represents the adjusted output voltage perturbation step length of the th power increase period, represents the actual output power change rate in the th power increase period, represents the maximum actual output power change rate extracted from the actual output power change rates in each regulation period to be regulated, represents the initial output voltage perturbation step length of the th power increase period, It represents the adjustment multiple of the output voltage disturbance step when the output power extracted from the database increases.

[0056] It should also be noted that the writing explanation of the above formula is as follows: In the formula is the starting point of adjustment. It represents the basic step without considering the power change rate and is the reference value of the entire adjustment model. , this step is the normalization process to ensure that the power change rates in different time periods are compared on a unified scale, avoiding out-of-control adjustment due to excessive numerical differences. is the key adjustment parameter, which amplifies the influence of the normalized power change rate on the step.

[0057] In a specific embodiment of the present invention, assume that there are three power increase time periods, and assume , , according to the data in Table 1 below, the adjusted output voltage disturbance steps for the assumed three power increase time periods can be calculated:

[0058] Table 1 Output data for power increase time periods

[0059]

[0060] Based on the data in Table 1, the adjusted output voltage disturbance step for the first power increase time period can be obtained as: , the adjusted output voltage disturbance step for the second power increase time period is: , the adjusted output voltage disturbance step for the third power increase time period is: , combining the above data, it can be obtained that when the initial steps are the same, the greater the power change rate, the greater the adjusted step. For example, the initial steps of the first and third power increase time periods are different, but by comparison, when the actual output power change rates are the same, the third power increase time period with a larger initial step also has a larger adjusted step.

[0061] E3. When the actual output power change rate of the photovoltaic module in a certain time period to be regulated is less than 0, then this time period to be regulated is recorded as a power reduction time period, and the output voltage disturbance step is adjusted for each power reduction time period.

[0062] In a specific embodiment of the present invention, the specific process of adjusting the output voltage disturbance step for each power reduction time period is as follows: When the actual output power of the photovoltaic module decreases as the monitoring time point progresses, it indicates that the current disturbance direction of the output voltage of the photovoltaic module is incorrect, and the operating point has crossed the maximum power point. It is necessary to immediately change the disturbance direction, and the adjusted output voltage disturbance step for each power reduction time period is obtained through comprehensive processing based on the actual output power change rate and the initial output voltage disturbance step of the power reduction time period.

[0063] It should be noted that the specific formula for comprehensively processing to obtain the adjusted output voltage disturbance step length in each power reduction time period is as follows: , where represents the number of the power reduction time period, , represents the number of power reduction time periods, represents the adjusted output voltage disturbance step length of the th power increase time period, represents the actual output power change rate in the th power reduction time period, represents the maximum value of the absolute value of the actual output power change rate, represents the initial output voltage disturbance step length of the th power reduction time period, represents the adjustment multiple of the output voltage disturbance step length when the output power decreases, which is extracted from the database.

[0064] It should also be noted that the explanation of the writing idea of the above formula is as follows: is the initial disturbance step length of the power reduction time period and serves as the basis for adjustment. By normalizing the absolute value of the power change rate, it reflects the relative amplitude of the current power drop. The greater the power drop amplitude, the more serious the disturbance deviation, and the step length needs to be reduced more significantly. At the same time, the denominator is to uniformly measure the severity of the power change. Whether the power increases or decreases, only the magnitude of the change is concerned. As the adjustment multiple, it amplifies the influence of the normalized power change rate on the step length, realizing the control logic of "the more obvious the power drop, the more significant the step length reduction", and quickly correcting the operating point to return to the maximum power point.

[0065] It should also be noted that the absolute value of the actual output power change rate of the photovoltaic module in each time period to be regulated is obtained, and the maximum value of the absolute value of the actual output power change rate is extracted from the absolute values of the actual output power change rates in each time period to be regulated.

[0066] In a specific embodiment of the present invention, it is assumed that there are three power reduction time periods, and it is assumed that , . According to the data in Table 2 below, the adjusted output voltage disturbance step lengths of the three assumed power reduction time periods can be calculated:

[0067] Table 2 Output data of power reduction time period

[0068]

[0069] Based on the data in Table 2, the adjusted output voltage perturbation step size for the first power reduction time period can be obtained as follows: , and the adjusted output voltage perturbation step size for the second power reduction time period is: , and the adjusted output voltage perturbation step size for the third power reduction time period is: , so according to the data in the above table, it can be obtained that the larger the absolute value of the actual output power change rate, the smaller the adjusted step size. For example, the absolute value of the actual output power change rate and the initial output voltage perturbation step size in the third power reduction time period are both the largest, but the reduction amplitude of the adjusted step size is the largest, reflecting the control logic of "the greater the power drop amplitude, the more significant the step size reduction".

[0070] E4. When in a certain time period to be regulated, first determine whether the time period to be regulated is a power increase time period or a power reduction time period. If it is a power increase time period, then use the adjusted output voltage perturbation step size of this power increase time period as a control signal and input it into the drive circuit of the photovoltaic module. If it is a power reduction time period, then use the adjusted output voltage perturbation step size of this power reduction time period as a control signal and input it into the drive circuit of the photovoltaic module, so as to realize the regulation of the output voltage of the photovoltaic module.

[0071] In the embodiment of the present invention, by tracking the maximum power point according to the change rate of the actual output electric power of the photovoltaic module and dynamically adjusting the size of the output voltage perturbation step size in real time, it overcomes the problems of slow tracking speed and easy misjudgment of the traditional perturbation observation method and conductance increment method when the light intensity changes rapidly, and enables the photovoltaic module to work at the maximum power point in a timely and accurate manner, thereby improving the power generation efficiency of the photovoltaic module.

[0072] In a specific embodiment of the present invention, a database is used in the execution process to store the output power loss rate corresponding to the unit influence factor, store the adjustment multiple of the output voltage perturbation step size when the output power increases, and store the adjustment multiple of the output voltage perturbation step size when the output power decreases.

[0073] The above content is only an example and explanation of the concept of the present invention. Those skilled in the art of the present technology make various modifications or supplements to the described specific embodiments or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they should all belong to the protection scope of the present invention.

Claims

1. An intelligent regulation method for a photovoltaic power generation system, characterized in that, It includes the following steps: S1. Collect the surface light intensity and surface temperature of the photovoltaic modules in the target photovoltaic power generation park corresponding to each monitoring time period, collect the surface images of the photovoltaic modules, and extract the service life, historical maintenance times and the time points of each maintenance of the photovoltaic modules; S2. Extract the characteristic curves corresponding to the photovoltaic modules in the target photovoltaic power generation park, and confirm the output power corresponding to the theoretically maximum power point of the photovoltaic modules in each monitoring time period; S3. Extract the output voltage and output current corresponding to each monitoring time point in each monitoring time period of the photovoltaic modules, and judge whether the operation of the photovoltaic modules in each monitoring time period is at the maximum power point. If not, execute step S4. Otherwise, it indicates that there is no need to perform step size regulation based on the actual output power change rate in the intelligent variable step size MPPT algorithm; S4. Record the monitoring time periods when the operation is not at the maximum power point as the time periods to be regulated, extract the initial output voltage perturbation step sizes of each time period to be regulated, and start the step size regulation process based on the actual output power change rate in the intelligent variable step size MPPT algorithm; The specific process of confirming the output power corresponding to the theoretically maximum power point of the photovoltaic modules in each monitoring time period is as follows: A1. Substitute the surface light intensity and surface temperature of the photovoltaic modules corresponding to each monitoring time period into the characteristic curves corresponding to the photovoltaic modules in the target photovoltaic power generation park to find the uncorrected output power corresponding to the theoretically maximum power point; A2. Calculate the influence factor corresponding to the output power at the theoretically maximum power point of the photovoltaic module through fusion calculation based on the surface image, service life, historical maintenance times, and time points of each maintenance of the photovoltaic module , and multiply it by the output power loss amount corresponding to the unit influence factor stored in the database to obtain the output power loss amount; A3. Subtract the output power loss from the uncorrected output power corresponding to the theoretically maximum power point of the photovoltaic modules in each monitoring time period to obtain the output power corresponding to the theoretically maximum power point of the photovoltaic modules in each monitoring time period; The calculation The specific process is as follows: B1. Perform coupling processing on the number of surface dirt areas located in the surface image of the photovoltaic module and the dirt area of each dirt area to obtain the surface dirt degree of the photovoltaic module, and perform aging analysis on the service life, historical maintenance times and the time points of each maintenance of the photovoltaic module to obtain the aging degree of the photovoltaic module; B2. Obtained by performing fusion calculation based on the surface dirtiness and aging degree of the photovoltaic module .

2. The intelligent control method of a photovoltaic power generation system according to claim 1, wherein: The specific process of obtaining the aging degree of the photovoltaic module is as follows: C1. Compare the time points of each maintenance of the photovoltaic module adjacent to each other to obtain the interval duration corresponding to each maintenance of the photovoltaic module, and extract the minimum value therefrom as the maintenance interval duration of the photovoltaic module; C2. Perform dynamic difference calculation on the maintenance interval duration, historical maintenance times and service life of the photovoltaic module respectively with the corresponding preset reference values, and perform normalization processing on each dynamic difference and then accumulate them to obtain the aging degree of the photovoltaic module.

3. The intelligent control method of a photovoltaic power generation system according to claim 1, characterized in that: The specific process of judging whether the operation of the photovoltaic modules in each monitoring time period is at the maximum power point is as follows: D1. Multiply the output voltage and output current corresponding to each monitoring time point in each monitoring time period of the photovoltaic modules to obtain the actual output power corresponding to each monitoring time point in each monitoring time period of the photovoltaic modules, and perform mean calculation on them to obtain the actual output power corresponding to each monitoring time period of the photovoltaic modules; D2. Compare the actual output power of the photovoltaic module corresponding to each monitoring time period with the output power corresponding to the theoretical maximum power point of the photovoltaic module in each monitoring time period. If the actual output power of the photovoltaic module corresponding to a certain monitoring time period is greater than or equal to the output power corresponding to the theoretical maximum power point of this monitoring time period, it indicates that the operation of the photovoltaic module in this monitoring time period is at the maximum power point; otherwise, it indicates that the operation of the photovoltaic module in this monitoring time period is not at the maximum power point.

4. The intelligent control method of a photovoltaic power generation system according to claim 3, wherein: The step regulation process for starting based on the actual output power change rate in the intelligent variable step size MPPT algorithm is as follows: E1. Analyze the change rate of the actual output power corresponding to each monitoring time point of the photovoltaic module in each regulation time period to obtain the actual output power change rate of the photovoltaic module in each regulation time period. E2. When the actual output power change rate of the photovoltaic module in a certain regulation time period is greater than 0, mark this regulation time period as a power increase time period, and adjust the output voltage perturbation step size for each power increase time period. E3. When the actual output power change rate of the photovoltaic module in a certain regulation time period is less than 0, mark this regulation time period as a power decrease time period, and adjust the output voltage perturbation step size for each power decrease time period. E4. When in a certain regulation time period, first determine whether this regulation time period is a power increase time period or a power decrease time period. If it is a power increase time period, use the adjusted output voltage perturbation step size of this power increase time period as the control signal and input it into the drive circuit of the photovoltaic module; if it is a power decrease time period, use the adjusted output voltage perturbation step size of this power decrease time period as the control signal and input it into the drive circuit of the photovoltaic module, so as to realize the regulation of the output voltage of the photovoltaic module.

5. The intelligent control method of a photovoltaic power generation system according to claim 4, characterized in that: The specific process for calculating the actual output power change rate of the photovoltaic module in each regulation time period is as follows: F1. Obtain the relative change rate of the actual output power corresponding to adjacent monitoring time points of the photovoltaic module in each regulation time period. F2. Sum up the relative change rates of the actual output power corresponding to all adjacent monitoring time points, and then divide by the number of monitoring time point intervals to obtain the actual output power change rate of the photovoltaic module in each regulation time period.

6. The intelligent control method of a photovoltaic power generation system according to claim 4, characterized in that: The specific process for adjusting the output voltage perturbation step size for each power increase time period is as follows: When the actual output power of the photovoltaic module increases as the monitoring time point progresses, it indicates that the current perturbation direction of the output voltage of the photovoltaic module is correct, and the operating point is moving towards the maximum power point. In order to accelerate the speed of the operating point moving towards the maximum power point, adjust the output voltage perturbation step size according to the actual output power change rate and the initial output voltage perturbation step size of the power increase time period to obtain the adjusted output voltage perturbation step size for each power increase time period.

7. The intelligent control method of a photovoltaic power generation system according to claim 4, characterized in that: The specific process of adjusting the output voltage perturbation step for each power reduction time period is as follows: When the actual output power of the photovoltaic module decreases as the monitoring time point progresses, it indicates that the current perturbation direction of the output voltage of the photovoltaic module is incorrect, and the operating point has crossed the maximum power point. It is necessary to immediately change the perturbation direction, and the adjusted output voltage perturbation step for each power reduction time period is obtained through comprehensive processing based on the actual output power change rate and the initial output voltage perturbation step during the power reduction time period.

8. The intelligent control method for a photovoltaic power generation system according to claim 1, characterized in that: The method uses a database during its execution to store the output power loss rate corresponding to the unit impact factor, the adjustment multiple of the output voltage perturbation step when the output power increases, and the adjustment multiple of the output voltage perturbation step when the output power decreases.

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