Intelligent control method for photovoltaic grid-connected inverter

Abstract

This invention discloses an intelligent control method for a photovoltaic grid-connected inverter, relating to the field of photovoltaic power generation technology. The method includes the following steps: system check, maximum power point tracking (MPPT), real-time measurement of the output voltage and current of the photovoltaic array in the photovoltaic system, obtaining ΔP(K) using an incremental algorithm, and then using the MPPT algorithm to obtain P based on ΔP(K). max (K) Grid-connected control connects the inverter to the grid, enabling intelligent power adjustment. After grid connection, the inverter output is adjusted through a power optimization algorithm to bring it closer to the theoretical maximum power point. Safety maintenance measures include an incremental algorithm that calculates power increments in real time and updates the maximum power point accordingly, improving the accuracy of tracking the maximum power point and ensuring that the photovoltaic system can operate close to the maximum power point. The power optimization algorithm then adjusts the inverter output to bring it closer to the theoretical maximum power point, achieving real-time optimization and improving the overall performance and efficiency of the photovoltaic system.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic power generation technology, specifically to an intelligent control method for photovoltaic grid-connected inverters. Background Technology

[0002] With economic and social development, solar energy, with its inexhaustible nature and environmental advantages, has become one of the most promising new energy sources both domestically and internationally. Grid-connected photovoltaic (PV) power generation directly connects the PV power generation system to the power grid, eliminating the need for bulky, expensive, and difficult-to-maintain batteries. As a key component of the PV grid-connected power generation system, the performance of the grid-connected inverter is crucial for improving PV power generation efficiency and reducing costs. The PV grid-connected inverter is the energy conversion link in the solar power generation system, influencing and determining whether the entire PV grid-connected system can operate stably, safely, reliably, and efficiently.

[0003] Current photovoltaic grid-connected inverter control methods do not consider changes in equipment operating parameters when tracking the maximum power point, resulting in low accuracy in tracking the maximum power point. Furthermore, the output of the photovoltaic grid-connected inverter cannot be adjusted according to the actual operating conditions and cannot be optimized in real time, leading to low efficiency of the photovoltaic system and energy loss. Summary of the Invention

[0004] The purpose of this invention is to provide an intelligent control method for photovoltaic grid-connected inverters, which solves the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: an intelligent control method for a photovoltaic grid-connected inverter, comprising the following steps:

[0006] System check: After the inverter is powered on, a self-test of the photovoltaic system is performed to ensure that all components are working properly. The voltage, frequency and phase angle of the grid are measured to confirm that the grid status meets the grid connection conditions.

[0007] Maximum power point tracking (MPPT) involves real-time measurement of the output voltage and current of the photovoltaic array in a photovoltaic system. An incremental algorithm is used to obtain the power increment ΔP(K) for the Kth iteration. Then, the MPPT algorithm is applied to obtain the maximum power point P for the Kth iteration based on the power increment ΔP(K). max (K);

[0008] Grid connection control connects the inverter to the grid by controlling the inverter's output frequency, phase, and voltage to synchronize it with the grid. During the synchronization process, the inverter's output power is gradually increased until it is fully connected to the grid.

[0009] Intelligent power regulation: After the inverter is connected to the grid, it monitors the grid voltage, current, phase and its own output power in real time, and adjusts the inverter output through power optimization algorithm to make it close to the theoretical maximum power point, thereby improving system efficiency.

[0010] Safety maintenance measures include setting up overload protection, short circuit protection, and over-temperature protection, and regularly conducting system inspections and maintenance to ensure long-term stable operation.

[0011] Optionally, the incremental algorithm process is as follows:

[0012] ;

[0013] Where ΔP(K) is the power increment in the Kth iteration;

[0014] α is the incremental factor adjustment coefficient, with an initial value of 0.7;

[0015] V in (K) Input voltage in the Kth iteration;

[0016] V in (K-1) is the input voltage of the K-1th iteration;

[0017] I in (K) Input current in the Kth iteration;

[0018] The specific process is as follows:

[0019] By taking into account the changes in voltage difference and current, ΔP(K) can more accurately calculate the power increment and gradually adjust the power, thereby improving the accuracy of maximum power point tracking.

[0020] Optionally, the maximum power point tracking algorithm process is as follows:

[0021] ;

[0022] Where P max (K) is the maximum power point in the Kth iteration;

[0023] P max (K-1) is the maximum power point in the K-1th iteration;

[0024] ΔP(K) is the power increment in the Kth iteration;

[0025] V in (K) Input voltage in the Kth iteration;

[0026] V ref (K) The reference voltage for the Kth iteration;

[0027] β is the voltage difference influence coefficient;

[0028] It is a correction item;

[0029] The specific process is as follows:

[0030] By combining ΔP(K) to gradually update the maximum power point, overshoot and stability issues caused by overcompensation are avoided, resulting in greater stability when tracking the maximum power point.

[0031] Optionally, the power optimization algorithm process is as follows:

[0032] ;

[0033] Where ΔP opt (K) is the power optimization adjustment amount in the Kth iteration;

[0034] c is the influence coefficient of the optimization adjustment amount;

[0035] P max (K) is the maximum power point in the Kth iteration;

[0036] P act (K) is the actual power output in the Kth iteration;

[0037] γ is the voltage change influence coefficient;

[0038] V in (K) is the output voltage of the Kth iteration;

[0039] V in (K-1) is the output voltage of the K-1th iteration;

[0040] It is the voltage variation coefficient;

[0041] set up The threshold Y is:

[0042] ;

[0043] Where V max It is the maximum voltage.

[0044] V min It is the minimum voltage value;

[0045] V nom It is the rated voltage;

[0046] ΔP is obtained through a power optimization algorithm. opt (K) is used to adjust the inverter output and, after multiple iterations, bring it close to the theoretical maximum power point, thereby improving system efficiency;

[0047] when When the value is greater than the threshold Y, α in the incremental algorithm changes, specifically:

[0048] .

[0049] Optionally, the iteration in the power optimization algorithm stops when the power increment change B is within a set range. Iteration stops when the power increment change B is less than 1%, at which point the system is close to the maximum power point. The calculation process for the power increment change B is as follows:

[0050] ;

[0051] Where P is the power increment change;

[0052] ΔP opt (K) is the power optimization adjustment amount in the Kth iteration;

[0053] ΔP opt (K-1) is the power optimization adjustment amount in the K-1th iteration.

[0054] Optionally, the self-test of the photovoltaic system includes basic status checks, indicator light checks, and parameter display checks. The basic status check includes confirming that the inverter is correctly connected to the power supply and that the power indicator light is on. The indicator light check includes checking that after the inverter is powered on, the start indicator light should be constantly on, indicating that the inverter has started. It also checks whether any fault indicator lights are on. If a fault indicator light is on, it indicates that the inverter has a fault. The parameter display check checks the display of various parameters after the inverter is powered on, including input voltage, battery status, and output power.

[0055] Optionally, the inverter is equipped with a wireless communication module, which allows the inverter's communication status to be checked via a mobile phone or other communication devices, and the inverter uploads data to a monitoring platform via the wireless communication module for remote monitoring.

[0056] Optionally, the short-circuit protection in the safety maintenance measures includes installing a fuse in the circuit. When a short circuit occurs, the fuse will blow, cutting off the circuit and protecting the inverter. The over-temperature protection includes installing a temperature sensor to monitor the equipment temperature in real time and setting a temperature alarm function to remind the operator of abnormal equipment temperature for subsequent handling.

[0057] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0058] I. This invention comprehensively considers changes in voltage difference and current through an incremental algorithm, enabling more accurate calculation of power increments and gradual power adjustments to improve the accuracy of maximum power point tracking. Furthermore, the incremental factor adjustment coefficient α can adjust power oscillations caused by voltage and current fluctuations, resulting in more stable photovoltaic system operation and improved overall performance. By combining the maximum power point tracking algorithm with the incremental algorithm's power increments to gradually update the maximum power point, and using correction terms to adjust the impact of the incremental algorithm results, the power oscillations caused by voltage and current fluctuations are reduced, allowing the system to respond quickly to environmental changes. The aforementioned algorithms are interconnected, collectively improving the speed and accuracy of maximum power point tracking.

[0059] II. This invention obtains power optimization adjustment amounts through a power optimization algorithm combined with a maximum power point tracking algorithm to adjust the inverter output. After multiple iterations, it brings the inverter output closer to the theoretical maximum power point, thereby improving the operating efficiency of the photovoltaic system. By introducing a voltage change threshold and an optimization adjustment amount influence coefficient β, it can quickly respond to voltage fluctuations and rapidly adjust and optimize when the environment changes. This achieves the effect of adjusting according to actual operating conditions, ensuring that the photovoltaic system always operates close to the maximum power point. At the same time, the voltage change coefficient in the power optimization algorithm adjusts α in the incremental algorithm in real time, enabling the photovoltaic system to adjust only when the voltage change is significant, avoiding frequent adjustments caused by small voltage changes, reducing system fluctuations, improving overall stability, and strengthening the connection between algorithms. Together, they form an intelligent control system for the photovoltaic grid-connected inverter, ensuring the operating efficiency of the photovoltaic system and avoiding energy loss. Attached Figure Description

[0060] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0061] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0062] Example 1, please refer to Figure 1 As shown in the figure, this embodiment provides an intelligent control method for a photovoltaic grid-connected inverter, including the following steps:

[0063] System check: After the inverter is powered on, a self-test of the photovoltaic system is performed to ensure that all components are working properly. The voltage, frequency and phase angle of the grid are measured to confirm that the grid status meets the grid connection conditions.

[0064] Maximum power point tracking (MPPT) involves real-time measurement of the output voltage and current of the photovoltaic array in a photovoltaic system. An incremental algorithm is used to obtain the power increment ΔP(K) for the Kth iteration. Then, the MPPT algorithm is applied, and the maximum power point P for the Kth iteration is obtained based on ΔP(K). max (K);

[0065] Grid connection control: The inverter is connected to the grid by controlling the inverter's output frequency, phase and voltage to synchronize it with the grid. During the synchronization process, the inverter's output power is gradually increased until it is fully connected to the grid.

[0066] Intelligent power regulation: After the inverter is connected to the grid, it monitors the grid voltage, current, phase and its own output power in real time, and adjusts the inverter output through power optimization algorithm to make it close to the theoretical maximum power point, thereby improving system efficiency.

[0067] Safety maintenance measures include setting up overload protection, short circuit protection, and over-temperature protection, and regularly conducting system inspections and maintenance to ensure long-term stable operation.

[0068] Short circuit protection includes installing fuses in the circuit. When a short circuit occurs, the fuses will blow, cutting off the circuit and protecting the inverter. Over-temperature protection includes installing temperature sensors to monitor the equipment temperature in real time and setting a temperature alarm function to alert operators to abnormal equipment temperatures for subsequent handling.

[0069] In this embodiment, the system performs self-checks to ensure all components are functioning normally and measures the grid voltage, frequency, and phase angle in real time to confirm that the grid status meets the grid connection conditions. This allows for timely detection and resolution of problems, ensuring stable intelligent control of the photovoltaic grid-connected inverter. An incremental algorithm is used to calculate power increments in real time and update the maximum power point accordingly, improving the accuracy of tracking the maximum power point and ensuring the photovoltaic system operates close to its maximum power point. By precisely controlling the inverter's output frequency, phase, and voltage, the output power is gradually increased during grid connection, ensuring smooth grid connection and improving stability. A power optimization algorithm monitors in real time and adjusts the inverter output based on actual operating conditions to bring it closer to the theoretical maximum power point, achieving real-time optimization and improving the overall performance and efficiency of the photovoltaic system.

[0070] Furthermore, the incremental algorithm process is as follows:

[0071] ;

[0072] Where ΔP(K) is the power increment in the Kth iteration;

[0073] α is the incremental factor adjustment coefficient, with an initial value of 0.7;

[0074] Vin (K) Input voltage in the Kth iteration;

[0075] V in (K-1) is the input voltage of the K-1th iteration;

[0076] I in (K) Input current in the Kth iteration;

[0077] Specifically, ΔP(K) can more accurately calculate the power increment by comprehensively considering the changes in voltage difference and current. By gradually adjusting the power, it can improve the accuracy of maximum power point tracking. Furthermore, the incremental factor adjustment coefficient α can adjust the power oscillation caused by voltage and current fluctuations, making the photovoltaic system operate more stably and improving the overall performance.

[0078] Furthermore, the maximum power point tracking algorithm process is as follows:

[0079] ;

[0080] Where P max (K) is the maximum power point in the Kth iteration;

[0081] P max (K-1) is the maximum power point in the K-1th iteration;

[0082] ΔP(K) is the power increment in the Kth iteration;

[0083] V in (K) Input voltage in the Kth iteration;

[0084] V ref (K) The reference voltage for the Kth iteration;

[0085] β is the voltage difference influence coefficient;

[0086] It is a correction term used to adjust the degree of influence of ΔP(K);

[0087] The specific process is as follows:

[0088] By combining ΔP(K) to gradually update the maximum power point, overshoot and stability issues caused by overcompensation are avoided, resulting in greater stability when tracking the maximum power point.

[0089] Specifically, by using dynamic ΔP(K), power output fluctuations and system oscillations caused by over-adjustment are effectively reduced, thus improving stability. This is achieved by real-time monitoring of data in the photovoltaic system and fully considering the input voltage V in the Kth iteration. in (K) and the reference voltage V in the Kth iteration ref(K) is calculated and a correction term is used. Adjusting the influence of ΔP(K) reduces power oscillations caused by voltage and current fluctuations, enabling the system to respond quickly to environmental changes and improving the speed and accuracy of maximum power point tracking.

[0090] Furthermore, the power optimization algorithm process is as follows:

[0091] ;

[0092] Where ΔP opt (K) is the power optimization adjustment amount in the Kth iteration;

[0093] c is the influence coefficient of the optimization adjustment amount;

[0094] P max (K) is the maximum power point in the Kth iteration;

[0095] P act (K) is the actual power output in the Kth iteration;

[0096] γ is the voltage change influence coefficient;

[0097] V in (K) is the output voltage of the Kth iteration;

[0098] V in (K-1) is the output voltage of the K-1th iteration;

[0099] It is the voltage variation coefficient;

[0100] set up The threshold Y is:

[0101] ;

[0102] Where V max It is the maximum voltage.

[0103] V min It is the minimum voltage value;

[0104] V nom It is the rated voltage;

[0105] Specifically, ΔP is obtained through a power optimization algorithm. opt(K) is used to adjust the inverter output and, after multiple iterations, bring it close to the theoretical maximum power point, thereby improving system efficiency. By introducing a voltage change threshold and optimizing the adjustment amount influence coefficient c, it can quickly respond to voltage fluctuations. This improved response speed helps the system to quickly adjust and optimize when the environment changes, achieving the effect of adjusting according to the actual operating conditions and ensuring that the photovoltaic system always operates close to the maximum power point.

[0106] when When the value is greater than the threshold Y, α in the incremental algorithm changes, specifically:

[0107] ;

[0108] Specifically, by adjusting α in the incremental algorithm in real time based on the voltage change coefficient, the photovoltaic system can only adjust when the voltage changes significantly, avoiding unnecessary frequent adjustments. This makes the adjustment process more efficient and accurate, reduces power fluctuations caused by over-adjustment, and lowers the system's energy consumption. When the voltage change does not reach the threshold, the system remains stable, avoiding frequent adjustments caused by small voltage changes, reducing system fluctuations, and improving overall stability.

[0109] Furthermore, the iteration in the power optimization algorithm stops when the power increment change B is within a set range. Iteration stops when the power increment change B is less than 1%, at which point the system is close to the maximum power point. The calculation process for the power increment change B is as follows:

[0110] ;

[0111] Where P is the power increment change;

[0112] ΔP opt (K) is the power optimization adjustment amount in the Kth iteration;

[0113] ΔP opt (K-1) is the power optimization adjustment amount in the K-1th iteration.

[0114] Specifically, by setting the range of power increment change B, the iteration is limited to avoid errors caused by infinite iteration. When the power increment change B is less than 1%, the iteration stops. At this point, the system is close to the maximum power point, and there is no need to perform the next iteration. At this point, the incremental algorithm, the maximum power point tracking algorithm, and the power optimization algorithm all stop, thereby saving calculation time and improving the working efficiency of the photovoltaic system.

[0115] Furthermore, the photovoltaic system self-test includes basic status checks, indicator light checks, and parameter display checks. The basic status check includes confirming that the inverter is correctly connected to the power supply and that the power indicator light is on. The indicator light check includes checking that after the inverter is powered on, the start indicator light should be constantly on, indicating that the inverter has started. It also checks whether any fault indicator lights are on. If a fault indicator light is on, it indicates that the inverter has a fault. The parameter display check is for inverters with digital screens, which display various parameters after power-on, including input voltage, battery status, and output power.

[0116] Specifically, through the photovoltaic system self-test, the inverter can conduct a comprehensive check on the internal hardware and software status at the initial stage of startup, ensuring that all components are working properly, avoiding system instability or shutdown due to equipment failure or configuration errors, improving the reliability of the photovoltaic system, and ensuring that the inverter can operate stably for a long time.

[0117] Furthermore, short-circuit protection in safety maintenance measures includes installing fuses in the circuit. When a short circuit occurs, the fuse will blow, cutting off the circuit and protecting the inverter. Over-temperature protection includes installing temperature sensors to monitor the equipment temperature in real time and setting a temperature alarm function to remind operators of abnormal equipment temperature for subsequent handling.

[0118] Specifically, safety maintenance measures ensure that the photovoltaic system can automatically disconnect or limit the current under abnormal conditions, preventing equipment damage or system failure and improving overall reliability. By preventing overload and overtemperature conditions, the stress and wear on the equipment can be reduced, extending the service life of the equipment. By effectively controlling power and heat, energy waste caused by failure or overload is reduced, improving the energy efficiency of the system. Safety maintenance measures reduce safety hazards caused by electrical faults and ensure the safety of operators and the surrounding environment of the equipment.

[0119] In Example 2, based on the above examples, the inverter is equipped with a wireless communication module, which allows the inverter's communication status to be checked via a mobile phone and other communication devices. The inverter can also upload data to a monitoring platform via the wireless communication module for remote monitoring.

[0120] By equipping the inverter with a wireless communication module, the inverter has remote monitoring and management functions. The inverter's operating status can be transmitted to a remote monitoring center via the network, allowing maintenance personnel to understand the inverter's status anytime, anywhere, and respond to fault alarms in a timely manner, thus improving the flexibility of the photovoltaic system.

[0121] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An intelligent control method for a photovoltaic grid-connected inverter, characterized in that, Includes the following steps: Step S1: System check. After the inverter is powered on, the photovoltaic system performs a self-check to ensure that all components are working properly and measures the voltage, frequency and phase angle of the grid to confirm that the grid status meets the grid connection conditions. Step S2: Maximum Power Point Tracking (MPPT) involves real-time measurement of the output voltage and current of the photovoltaic array in the photovoltaic system. The incremental algorithm is used to obtain the power increment ΔP(K) for the Kth iteration. The MPPT algorithm is then used to obtain the maximum power point P for the Kth iteration based on the power increment ΔP(K). max (K); Step S3: Grid connection control, connect the inverter to the grid, control the inverter's output frequency, phase and voltage to synchronize it with the grid, and gradually increase the inverter's output power until it is fully connected to the grid; Step S4: Intelligent power adjustment. After the inverter is connected to the grid, it monitors the voltage, current, phase of the grid and its own output power in real time, and uses a power optimization algorithm to adjust the inverter output to make it close to the maximum power point. Step S5: Safety maintenance measures, including setting up overload protection, short circuit protection, and over-temperature protection safety measures, and conducting regular system inspections and maintenance; The incremental algorithm formula is as follows: ； Where ΔP(K) is the power increment in the Kth iteration; α is the adjustment coefficient for the incremental factor, with an initial value of 0.7; V in (K) represents the input voltage in the Kth iteration; V in (K-1) is the input voltage of the K-1th iteration; I in (K) represents the input current in the Kth iteration; ΔP(K) calculates the power increment by taking into account the changes in voltage difference and current, and gradually adjusts the power to improve the accuracy of maximum power point tracking. The maximum power point tracking algorithm formula is as follows: ； Where P max (K) represents the maximum power point in the Kth iteration; P max (K-1) is the maximum power point in the K-1th iteration; ΔP(K) is the power increment in the Kth iteration; V in (K) represents the input voltage in the Kth iteration; V ref (K) is the reference voltage for the Kth iteration; β is the voltage difference influence coefficient; This is a correction item; By combining ΔP(K) to gradually update the maximum power point, overshoot and stability issues caused by overcompensation are avoided, resulting in greater stability when tracking the maximum power point.

2. The intelligent control method for a photovoltaic grid-connected inverter according to claim 1, characterized in that: The power optimization algorithm formula is as follows: ； Where ΔP opt (K) represents the power optimization adjustment amount in the Kth iteration; c represents the influence coefficient of the optimization adjustment amount; P max (K) represents the maximum power point in the Kth iteration; P act (K) represents the actual power output in the Kth iteration; γ is the voltage variation influence coefficient; V in (K) represents the output voltage of the Kth iteration; V in (K-1) is the output voltage of the K-1th iteration; The voltage variation coefficient; set up The threshold Y is: ； Where V max This is the maximum voltage value; V min This is the minimum voltage value; V nom Rated voltage; ΔP is obtained through a power optimization algorithm. opt (K) is used to adjust the inverter output and, after multiple iterations, bring it close to the theoretical maximum power point. when When the value is greater than the threshold Y, the formula for the change of the incremental factor adjustment coefficient α in the incremental algorithm is as follows: 。 3. The intelligent control method for a photovoltaic grid-connected inverter according to claim 2, characterized in that: The power optimization algorithm stops iterating when the power increment change B is less than 1%, at which point the system is close to the maximum power point. The specific formula for the power increment change B is as follows: ； Where P represents the power increment change; ΔP opt (K) represents the power optimization adjustment amount in the Kth iteration; ΔP opt (K-1) represents the power optimization adjustment amount in the K-1th iteration.

4. The intelligent control method for a photovoltaic grid-connected inverter according to claim 1, characterized in that: The self-test of the photovoltaic system includes basic status check, indicator light check and parameter display check; Basic status checks include confirming that the inverter is correctly connected to the power supply and that the power indicator light is on. Indicator light checks include checking that the start indicator light should be constantly on after the inverter is powered on, indicating that the inverter has started, checking if any fault indicator lights are on, and if any fault indicator lights are on, indicating that the inverter has a fault. Parameter display checks are performed on the display of various parameters after the inverter is powered on. The parameters include input voltage, battery status, and output power.

5. The intelligent control method for a photovoltaic grid-connected inverter according to claim 1, characterized in that: The inverter is equipped with a wireless communication module, which allows users to check the inverter's communication status via mobile phone and other communication devices. The inverter also uploads data to the monitoring platform via the wireless communication module.

6. The intelligent control method for a photovoltaic grid-connected inverter according to claim 1, characterized in that: The safety maintenance measures include short-circuit protection by installing fuses in the circuit. When a short circuit occurs, the fuses will blow, cutting off the circuit and protecting the inverter. Over-temperature protection includes installing temperature sensors to monitor the equipment temperature in real time and setting a temperature alarm function to remind operators of abnormal equipment temperature.

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