Power point tracking system for single-phase two-stage photovoltaic grid-connected inverter under shading conditions

Abstract

The single-phase two-stage photovoltaic grid-connected inverter power point tracking system under shading condition comprises a photovoltaic array module, a DC / DC module, an inverter module and a controller module; the photovoltaic array module generates electricity by using solar energy and outputs voltage; the DC / DC module amplifies the voltage output by the photovoltaic array module; the inverter module is connected with the DC / DC module and the controller module to convert the amplified voltage into alternating current; the controller module obtains the output power data, the illumination and the environmental temperature of the photovoltaic array module, and combines with an intelligent algorithm to quickly search the global maximum power point; according to the maximum power point, the DC / DC module is controlled to adjust the output voltage and the photovoltaic array module is controlled to adjust the working point, so that the output power of the photovoltaic module is close to the maximum power point, and the power point tracking is realized. The system improves the accuracy of tracking the maximum power point and avoids falling into a local extreme value.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of photovoltaic power generation, in particular to a power point tracking system under shading conditions for a single-phase two-stage photovoltaic grid-connected inverter. BACKGROUND

[0002] With the increasing shortage of world energy, the development and use of clean energy are paid more and more attention, among which photovoltaic power generation is the most widely used as the most stable clean energy. Photovoltaic power generation system is divided into off-grid photovoltaic power generation system and grid-connected photovoltaic power generation system. The grid-connected photovoltaic power generation system is connected to the grid through an inverter, and the power generation is realized through the cooperation between the grid and the inverter. The two-stage inverter increases the DC / DC converter, so that the power tracking and the inverter grid connection are independent of each other, and the control is more convenient. The characteristics of photovoltaic power generation are greatly affected by light conditions. When the light condition is stable, the system output has a maximum output power point, which is affected by environmental changes, and the corresponding voltage also changes. Finding the maximum power point, determining the corresponding voltage value, and adjusting it can make the system always work near the maximum power point, so that the conversion efficiency of the system can be the highest, which is of great significance to improve the power generation output efficiency of the photovoltaic power generation system.

[0003] The existing power point tracking system has the following defects: first, the photovoltaic power generation system is often subjected to a certain degree of shading in actual application, and the existing power tracking system is easy to fall into local extreme value, and it is difficult to achieve accurate tracking effect under shading conditions; second, when the environmental temperature changes, it will have a great impact on the output of the entire photovoltaic power generation system, and the steady-state error of the existing constant voltage tracking system is large, and the energy conversion efficiency is low; third, when the external environmental conditions change rapidly, the existing tracking system uses power feedback algorithm to determine the maximum power point, and the actual power point oscillates repeatedly, which may cause misjudgment, affecting the output efficiency of the system. SUMMARY

[0004] The main purpose of the present application is to overcome the above-mentioned defects in the prior art, and to provide a power point tracking system under shading conditions for a single-phase two-stage photovoltaic grid-connected inverter, which improves the accuracy of tracking the maximum power point and avoids falling into local extreme value.

[0005] The present application adopts the following technical scheme:

[0006] The single-phase two-stage photovoltaic grid-connected inverter power point tracking system under shading conditions comprises a photovoltaic array module, a DC / DC module, an inverter module and a controller module; the photovoltaic array module generates power by solar energy and outputs voltage; the DC / DC module amplifies the voltage output by the photovoltaic array module; the inverter module is connected with the control DC / DC module and the controller module to convert the amplified voltage into alternating current, characterized in that: the controller module obtains the output power data, the illumination and the ambient temperature of the photovoltaic array module, and quickly searches for the global maximum power point in combination with an intelligent algorithm, controls the DC / DC module to adjust the output voltage and controls the photovoltaic array module to adjust the working point, so that the output power of the photovoltaic module is close to the maximum power point, and power point tracking is realized.

[0007] The RBF neural network is used to search for the maximum power point, the RBF neural network comprises an input layer, a hidden layer and an output layer; the input layer inputs the illumination and the ambient temperature, the nodes of the hidden layer adopt Gaussian activation functions; two vectors input in the input layer are directly connected to each node of the hidden layer, the output H j of each node of the hidden layer is connected to the output Y k of the output layer.

[0008]

[0009] In the formula, f(.) is a Gaussian function, I i represents the i-th sample of the input sample set I, C j is a radial basis function center, r is a variance of the Gaussian function, C j ∈R; Y k is the maximum power point output by the RBF neural network; ω jk is an output weight; B0 is a bias, and Hj represents a duty cycle sample set through the Gaussian function in the hidden layer.

[0010] The RBF neural network is trained by using a gradient descent algorithm, so as to obtain an optimal output weight.

[0011] The PWM signal duty cycle value corresponding to the maximum power point output by the output layer is taken as a sample set, and a sample is randomly selected; an iteration counter is set to 0 and a maximum iteration number n is set, the real-time sample in the sample set is compared with the adjacent sample, and the maximum power point Y k, update the value of the iteration counter after each cycle, and stop the cycle when the number of iterations is greater than a preset maximum number of iterations; the real-time sample is a duty cycle value of a PWM signal corresponding to the current output maximum power point, and the adjacent sample is a duty cycle value of a PWM signal corresponding to the maximum power point predicted before and after the number of iterations is increased.

[0012] The DC / DC module is provided with a BOOST unit, and the BOOST unit is provided with an amplifier Q1. The controller module sets a step size according to the maximum power point and in combination with the change rate of power and voltage, and adjusts the duty cycle of the amplifier Q1 in the disturbance direction every other step size.

[0013] When the difference between the output power of the photovoltaic array module and the maximum power point is greater than a set threshold, a first step size is set; when the difference between the output power of the photovoltaic array module and the maximum power point is less than a set threshold, a second step size is set, and the second step size is less than the first step size.

[0014] The disturbance direction is determined according to the change of the output power of the photovoltaic array module, including increasing or decreasing the duty cycle of the amplifier Q1; the duty cycle of the amplifier Q1 is adjusted in the determined disturbance direction every other step size: if the output power increases, the duty cycle of the amplifier Q1 is continuously adjusted in the disturbance direction of the previous step size; if the output power decreases, the duty cycle of the amplifier Q1 is adjusted in the disturbance direction opposite to the previous step size.

[0015] The inverter module includes an inverter control unit, a full-bridge inverter circuit and a grid-connected filter. The full-bridge inverter circuit is connected to the output end of the DC / DC module to convert the output voltage into alternating current. The grid-connected filter is connected to the output end of the full-bridge inverter circuit to filter out high-frequency components in the output current. The inverter control unit is connected to the full-bridge inverter circuit and the grid-connected filter to output an SPWM signal to control the on-off of the switching tube of the full-bridge inverter circuit to realize the grid-connected inverter function according to the voltage and current double closed loop control strategy.

[0016] The inverter module further includes an overcurrent protection unit, an overvoltage protection unit, an undervoltage protection unit and a temperature protection unit. The overcurrent protection unit is connected to the full-bridge inverter circuit to adjust the output duty cycle to turn off the switching tube of the full-bridge inverter circuit to realize the overcurrent protection function when the detected value exceeds the set value. The overvoltage protection unit and the undervoltage protection unit sample the voltage value between the full-bridge inverter circuit and the DC / DC module in real time and adjust the output duty cycle to turn off the switching tube of the full-bridge inverter circuit to realize the overvoltage and undervoltage protection function when the voltage value exceeds the set range. The temperature protection unit adjusts the output duty cycle to turn off the switching tube of the full-bridge inverter circuit when the temperature exceeds the set value by collecting the ambient temperature of the full-bridge inverter circuit in real time.

[0017] The photovoltaic array module comprises a photovoltaic cell unit, a current sensing unit, a voltage sensing unit, a short circuit protection unit and an execution unit; the current sensing unit and the voltage sensing unit are connected with the photovoltaic cell unit to detect current information and voltage information of the photovoltaic cell unit, the short circuit protection unit is connected with the photovoltaic cell unit to realize short circuit protection, and the execution unit is connected with the photovoltaic cell unit to adjust the working point of the photovoltaic cell.

[0018] The system of the present application has the power point search and tracking independent of each other, avoids falling into local extreme value, and improves the accuracy of tracking the maximum power point; through the perturbation observation method, the power feedback method is used for real-time feedback tracking, the maximum power point can be adjusted in time under the condition of temperature change, the perturbation length is limited by setting the perturbation threshold value, and the problem that the perturbation is increased all the time under the condition of large environmental change, leading to the problem that it is difficult to lock the oscillation near the maximum power point. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 The system composition diagram of the present application is shown in the figure;

[0020] Figure 2 The circuit diagram of the present application is shown in the figure;

[0021] Figure 3 The logic block diagram of searching the maximum power point of the present application is shown in the figure;

[0022] Figure 4 The logic block diagram of perturbation observation of the present application is shown in the figure.

[0023] The present application will be further described in detail below in combination with the drawings and specific embodiments. DETAILED DESCRIPTION

[0024] The present application will be further described in detail below in combination with the drawings and specific embodiments.

[0025] In the present application, the terms "first", "second", "third" and the like are only used to distinguish similar objects, and do not have to be used to describe a specific order or sequence, and cannot be understood as indicating or implying relative importance. In the description, the directions or positions indicated by "up", "down", "left", "right", "front" and "back" are based on the directions or positions shown in the drawings, and are only for the convenience of describing the present application, and cannot be understood as indicating or implying that the device must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the scope of protection of the present application. For ordinary skilled persons in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0026] In addition, in the description of the present application, "a plurality of" refers to two or more, unless otherwise specified. The association relationship of the associated objects described by "and / or" indicates that there can be three relationships, for example, A and / or B can represent the three cases of A existing alone, A and B existing together, and B existing alone. The character " / " generally represents an "or" relationship between the associated objects before and after it.

[0027] Referring to Figure 1 , Figure 2 The single-phase two-stage photovoltaic grid-connected inverter power point tracking system of the present application mainly includes a photovoltaic array module, a DC / DC module, an inverter module, and a controller module. The photovoltaic array module uses solar power to generate electricity and outputs voltage. The DC / DC module amplifies the voltage output by the photovoltaic array module. The inverter module is connected to the DC / DC module and the controller module to convert the amplified voltage into alternating current. The controller module obtains the output power data, illumination, and environmental temperature of the photovoltaic array module, and quickly searches for the global maximum power point in combination with an intelligent algorithm. According to the maximum power point, the DC / DC module adjusts the output voltage and the photovoltaic array module adjusts the operating point, so that the output power of the photovoltaic module is close to the maximum power point, and power point tracking is achieved.

[0028] The photovoltaic array module includes a photovoltaic cell unit, a current sensing unit, a voltage sensing unit, a short circuit protection unit, and an execution unit. The current sensing unit and the voltage sensing unit are connected to the photovoltaic cell unit to detect the current and voltage information of the photovoltaic cell unit. The short circuit protection unit is connected to the photovoltaic cell unit to realize short circuit protection using a fuse. When the current detected by the current sensing unit is greater than the upper limit of the current corresponding to the fuse, the relevant circuit is short-circuited to realize short circuit protection, which is time-efficient. The execution unit is connected to the photovoltaic cell unit to adjust the operating point of the photovoltaic cell, which includes adjusting the output voltage and current of the photovoltaic cell unit, etc.

[0029] In actual application, the execution module is realized by a digital signal processor (DSP) F28335 as a central controller. The collected external signals (voltage, current, and temperature) are digitized, and then operated through the logic links in the drawings to output the duty cycle value to control the on-off time ratio of the switching tube, which in turn affects the input equivalent resistance of the BOOST circuit, and realizes the adjustment of the maximum power point by dividing the voltage in series with the internal resistance of the photovoltaic panel.

[0030] The DC / DC module is provided with a BOOST unit, a driving unit and an overload protection unit, the BOOST unit is used for boosting the voltage output by the photovoltaic array module, the BOOST includes a BOOST voltage converter composed of a capacitor C1, an inductor L1, a switch tube Q1, a diode D1 and a capacitor C2. The switch tube Q1 can receive the PWM signal output from the controller module to change the duty cycle. The driving unit is used to provide a suitable driving signal for the switch tube Q1 in the BOOST unit, and the overload protection unit is used to close the BOOST unit when the output current of the photovoltaic array module is too large, to avoid overheating or damage.

[0031] The inverter module includes an inverter control unit, a full-bridge inverter circuit and a grid-connected filter. Among them, the full-bridge inverter circuit is connected with the output end of the DC / DC module to convert the output voltage into alternating current, which includes four switch tubes Q2, Q3, Q4 and Q5. The grid-connected filter is connected with the output end of the full-bridge inverter circuit to filter out the high-frequency components in the output current. The grid-connected filter adopts an LCL type filter to filter the output current on the inverter side. By selecting appropriate values, the high-frequency components in the output current are filtered out, the total harmonic distortion of the output current is reduced, and the quality of the output current is improved. The inverter control unit is connected with the full-bridge inverter circuit and the grid-connected filter. By collecting parameters such as grid voltage phase, inverter side current, DC current voltage, etc., and sending them into the inverter control unit for calculation and solution, according to the voltage and current double closed loop control strategy, the SPWM signal is output to control the on-off of the switch tubes of different bridge arms of the full-bridge inverter circuit to realize the grid-connected inverter function.

[0032] Further, the inverter module further includes an inverter protection unit, which includes an overcurrent protection circuit, an overvoltage protection circuit, an undervoltage protection circuit and a temperature protection circuit, etc., which are respectively used to realize overcurrent protection, overvoltage protection, undervoltage protection, temperature protection, etc.

[0033] Specifically, the over-current protection module compares the current value of the inductor L2 on the inverter side of the LCL type filter with the set upper limit in real time, and when the detected value exceeds the set value, the inverter control module turns off the switch tube of the full-bridge inverter circuit by adjusting the output duty cycle to realize the over-current protection function. The over-voltage protection module compares the voltage value on the DC bus capacitor C2 between the full-bridge inverter circuit and the boost unit for voltage stabilization with the set upper and lower limits in real time, and when the detected value exceeds the set upper limit or is lower than the set lower limit, the inverter control module turns off the switch tube of the full-bridge inverter circuit by adjusting the output duty cycle to realize the over-voltage and under-voltage protection function; the temperature protection unit compares the ambient temperature at the heat sink of the switch tube Q1-Q4 in the full-bridge inverter circuit with the set upper limit in real time, and when the detected value exceeds the set value, the inverter control module turns off the switch tube of the full-bridge inverter circuit by adjusting the output duty cycle to realize the over-temperature protection function, preventing damage to the switch tube.

[0034] In the present application, the inverter control unit can also realize grid-connected detection and island detection, avoid power grid failure, cause the photovoltaic array module and the load module to form an independent power supply island, and incorporate the detected electric energy into the power grid module and supply energy for the load module.

[0035] When using the present application for power point tracking under shading conditions, first, the photovoltaic cell unit in the photovoltaic array module generates electricity, and since the output voltage value of the photovoltaic array module is low, the boost unit in the DC / DC module 2 is needed to step up the voltage to lift the DC bus voltage to 380VDC-420VDC to meet the requirements of grid-connected inversion.

[0036] The controller module obtains the output power change data of the photovoltaic array module by obtaining the current sensing unit and the voltage sensing unit, and obtains the illumination and environmental temperature of the photovoltaic array module in real time, and then searches for the global maximum power point quickly in combination with intelligent algorithm search, avoiding falling into local extreme value.

[0037] Specifically, the present application uses RBF neural network to search for the maximum power point, and the RBF neural network includes an input layer, a hidden layer and an output layer. The input layer inputs the illumination and the environmental temperature, and the target output is the maximum power point Y k of the photovoltaic output under the current shadow shielding condition. The hidden layer nodes are composed of different activation functions, thereby learning the nonlinear relationship in the data, and the nodes of the hidden layer in the present application use Gaussian activation function. The two vectors input in the input layer are directly connected to each node of the hidden layer, and the output H j of the hidden layer node is connected to the output Y k of the output layer as shown in the following formula:

[0038]

[0039] wherein: f(.) is a Gaussian function, I i represents the i-th sample of the input sample set I, C j is a radial basis function center, r is a variance of the Gaussian function, C j ∈R; Y k is a maximum power point output by the RBF neural network; ω jk is an output weight; B0 is a bias, and Hj represents a duty cycle sample set mapped in a hidden layer through a Gaussian function.

[0040] The RBF neural network is trained by using a gradient descent algorithm, so that the optimal output weight is obtained.

[0041] The maximum power point output by the output layer is taken as a sample set, and a sample is randomly selected; an iteration counter is set to 0 and a maximum iteration number n is set; the maximum power point Y k predicted by the RBF neural network is updated in real time by comparing a real-time sample in the sample set with a neighboring sample, the value of the iteration counter is updated after each loop, and the loop is stopped when the iteration number is greater than the preset maximum iteration number. The real-time sample is a duty cycle value of a PWM signal corresponding to the maximum power point output at present, and the neighboring sample is a duty cycle value of a PWM signal corresponding to the maximum power point predicted before and after the iteration number is increased.

[0042] Further, referring to Figure 3 the maximum power point Y k predicted by the RBF neural network is updated in real time by comparing a real-time sample in the sample set with a neighboring sample, the value of the iteration counter is updated after each loop, and the loop is stopped when the iteration number is greater than the preset maximum iteration number. The real-time sample is a duty cycle value of a PWM signal corresponding to the maximum power point output at present, and the neighboring sample is a duty cycle value of a PWM signal corresponding to the maximum power point predicted before and after the iteration number is increased.

[0043] 1) a sample in the sample set is randomly selected as a present sample;

[0044] 2) another sample is randomly selected and compared with the present sample, if the another sample is greater than the present sample, the another sample is set as the present sample, the step is repeated, and if not, 3) is entered;

[0045] 3) a real-time sample in the sample set is selected and compared with the present sample, if the real-time sample is greater than the present sample, the real-time sample is taken as the present sample, the step is repeated, and if not, 4) is entered;

[0046] 4) a neighboring sample in the sample set is selected and compared with the present sample, if the neighboring sample is greater than the present sample, the step is repeated, and if not, it is judged whether the iteration number is greater than the preset maximum iteration number, if yes, 1) is entered, and if not, the present sample corresponding search maximum power point is output.

[0047] Referring toFigure 4 The controller module sets a step length according to the maximum power point and in combination with the change rate of power and voltage when performing maximum power point tracking, and adjusts the duty cycle of the amplifier Q1 in the perturbation direction every step length. The step length is set quantitatively by the perturbation, the change rate of power to voltage is calculated to determine the distance to the maximum power point, and then a suitable step length is selected. The rule is that when the working point of the photovoltaic array module deviates from the maximum power point, the perturbation quantitative module outputs a larger step length; when the working point is close to the maximum power point, the perturbation quantitative module outputs a smaller step length.

[0048] Specifically, when the difference between the output power of the photovoltaic array module and the maximum power point is greater than a set threshold, a first step length is set; when the difference between the output power of the photovoltaic array module and the maximum power point is less than a set threshold, a second step length is set, and the second step length is smaller than the first step length. When the power change of the photovoltaic array module output is less than the threshold range, it can be determined that the system has tracked to the maximum power point, and the problem of oscillation near the maximum power point caused by continuous increase of perturbation is avoided.

[0049] The controller module of the present application can also realize perturbation observation, which determines the perturbation reversal according to the change of the output power of the photovoltaic array module, including controlling the increase or decrease of the duty cycle of the amplifier Q1. The duty cycle of the amplifier Q1 is adjusted in the determined perturbation direction every step length, thereby increasing or decreasing the output voltage of the photovoltaic array module, and observing the feedback power change of the photovoltaic array module. According to the feedback power change, the next control signal is determined: if the output power increases, the duty cycle of the amplifier Q1 is adjusted in the perturbation direction of the previous step length; if the output power decreases, the duty cycle of the amplifier Q1 is adjusted in the perturbation direction opposite to the previous step length. In this way, the actual working point of the photovoltaic array module can gradually approach the searched maximum power point, and finally reach a steady state in a smaller range near the maximum power point.

[0050] The controller module of the present application also sends a control signal to adjust the working point of the photovoltaic array module, so as to adjust the working voltage and current to approach the maximum power point. The output voltage after adjustment is boosted by the DC / DC module, the current after boosting enters the inverter module for inversion, including receiving direct current, and performing voltage stabilization, current stabilization and isolation processing. Then, the direct current is converted into alternating current, the alternating current after conversion is filtered to remove harmonics and high-frequency interference, and then grid-connected detection and island detection are performed to avoid the photovoltaic array module and the load module forming an independent power supply island when the power grid fails. The detected electric energy is connected to the power grid module and supplies energy to the load module.

[0051] The controller module of the present application can also monitor environmental conditions, record system operation log information, store power point tracking data, and transmit power point tracking data.

[0052] The above merely illustrates the specific embodiments of the present application, but the design concept of the present application is not limited thereto, and any non-essential modification of the present application using the concept shall be deemed as the infringement of the protection scope of the present application.

Claims

1. A power point tracking system for a single-phase two-stage photovoltaic grid-connected inverter under shading conditions, comprising a photovoltaic array module, a DC / DC module, an inverter module, and a controller module; wherein the photovoltaic array module generates electricity using solar energy and outputs voltage; the DC / DC module amplifies the voltage output by the photovoltaic array module; and the inverter module is connected to the DC / DC module and the controller module to convert the amplified voltage into alternating current, characterized in that: The controller module acquires the output power data, illuminance, and ambient temperature of the photovoltaic array module, and combines them with an intelligent algorithm to quickly search for the global maximum power point. Based on the maximum power point, it controls the DC / DC module to adjust the output voltage and the photovoltaic array module to adjust the operating point, so that the output power of the photovoltaic module is close to the maximum power point, thereby achieving power point tracking. An RBF neural network is used to search for the maximum power point. The RBF neural network includes an input layer, a hidden layer, and an output layer. The input layer takes the illuminance and ambient temperature as inputs, and the nodes in the hidden layer use a Gaussian activation function. The two vectors input to the input layer are directly connected to each node in the hidden layer, and the output H of each hidden layer node... j With the output layer output Y k As shown in the following formula: ； ； In the formula: f(.) is the Gaussian function, This represents the i-th sample in the input sample set I. is the center of the radial basis functions, and r is the variance of the Gaussian function. ∈R; The maximum power point output by the RBF neural network; For output weights; For bias; The duty cycle value of the PWM signal corresponding to the maximum power point output by the output layer is used as a sample set, and samples are randomly selected; the iteration counter is set to 0 and the maximum number of iterations n is set. The maximum power point Y predicted by the RBF neural network is updated in real time by comparing the real-time samples in the sample set with adjacent samples. k After each loop, the value of the iteration counter is updated. When the number of iterations exceeds the preset maximum number of iterations, the loop stops. The real-time sample is the duty cycle value of the PWM signal corresponding to the current maximum power point. The adjacent sample refers to the duty cycle value of the PWM signal corresponding to the maximum power point predicted before and after the number of iterations increases. The DC / DC module is equipped with a BOOST unit, which is equipped with an amplifier tube Q1. The controller module sets a step size based on the maximum power point and the rate of change of power and voltage. Every step size, the duty cycle of the amplifier tube Q1 is adjusted according to the direction of the disturbance. When the difference between the output power of the photovoltaic array module and the maximum power point is greater than a set threshold, the first step size is set. When the difference between the output power of the photovoltaic array module and the maximum power point is less than a set threshold, a second step size is set, which is less than the first step size.

2. The power point tracking system for a single-phase two-stage photovoltaic grid-connected inverter under shading conditions as described in claim 1, characterized in that: The RBF neural network is trained using the gradient descent algorithm to obtain the optimal output weights.

3. The power point tracking system for a single-phase two-stage photovoltaic grid-connected inverter under shading conditions as described in claim 1, characterized in that: The perturbation direction is determined based on the change in the output power of the photovoltaic array module, including increasing or decreasing the duty cycle of the amplifier tube Q1; the duty cycle of the amplifier tube Q1 is adjusted according to the determined perturbation direction at every step: if the output power increases, the duty cycle of the amplifier tube Q1 is adjusted according to the perturbation direction of the previous step; if the output power decreases, the duty cycle of the amplifier tube Q1 is adjusted according to the perturbation direction opposite to that of the previous step.

4. The power point tracking system for a single-phase two-stage photovoltaic grid-connected inverter under shading conditions as described in claim 1, characterized in that: The inverter module includes an inverter control unit, a full-bridge inverter circuit, and a grid-connected filter. The full-bridge inverter circuit is connected to the output terminal of the DC / DC module to convert the output voltage into alternating current. The grid-connected filter is connected to the output terminal of the full-bridge inverter circuit to filter out high-frequency components in the output current. The inverter control unit is connected to the full-bridge inverter circuit and the grid-connected filter to output an SPWM signal based on a voltage and current dual closed-loop control strategy to control the switching of the switching transistors of the full-bridge inverter circuit to achieve the grid-connected inverter function.

5. The power point tracking system for a single-phase two-stage photovoltaic grid-connected inverter under shading conditions as described in claim 4, characterized in that: The inverter module also includes an overcurrent protection unit, an overvoltage protection unit, an undervoltage protection unit, and a temperature protection unit. The overcurrent protection unit is connected to the full-bridge inverter circuit to adjust the output duty cycle and shut down the switching transistors of the full-bridge inverter circuit when the detected value exceeds a set value, thereby achieving overcurrent protection. The overvoltage protection unit and the undervoltage protection unit sample the voltage value between the full-bridge inverter circuit and the DC / DC module in real time and adjust the output duty cycle to shut down the switching transistors of the full-bridge inverter circuit when the voltage value exceeds a set range, thereby achieving overvoltage and undervoltage protection. The temperature protection unit collects the ambient temperature of the full-bridge inverter circuit in real time and adjusts the output duty cycle to shut down the switching transistors of the full-bridge inverter circuit when the temperature exceeds a set value.

6. The power point tracking system for a single-phase two-stage photovoltaic grid-connected inverter under shading conditions as described in claim 1, characterized in that: The photovoltaic array module includes a photovoltaic cell unit, a current sensing unit, a voltage sensing unit, a short-circuit protection unit, and an execution unit. The current sensing unit and the voltage sensing unit are connected to the photovoltaic cell unit to detect the current and voltage information of the photovoltaic cell unit. The short-circuit protection unit is connected to the photovoltaic cell unit to achieve short-circuit protection. The execution unit is connected to the photovoltaic cell unit to adjust the operating point of the photovoltaic cell.

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