Intelligent control method of photovoltaic grid-connected inverter

Abstract

The invention discloses an intelligent control method of a photovoltaic grid-connected inverter, which relates to the technical field of photovoltaic power generation and comprises the following steps of: checking a system, tracking a maximum power point, measuring output voltage and current of a photovoltaic array in a photovoltaic system in real time, obtaining delta P (K) by using an incremental algorithm, obtaining Pmax (K) by using a maximum power point tracking algorithm according to the delta P (K), and performing grid-connected control. After the inverter is subjected to grid connection, intelligent power adjustment and grid connection, the output of the inverter is adjusted through a power optimization algorithm to be close to a theoretical maximum power point and safety maintenance measures, the power increment is calculated in real time through an increment algorithm, and the maximum power point is updated based on the increment algorithm, so that the accuracy of tracking the maximum power point is improved; according to the method, the photovoltaic system can run close to the maximum power point, and the output of the inverter is adjusted through a power optimization algorithm, so that the inverter is close to the theoretical maximum power point, real-time optimization is realized, and the overall performance and the working efficiency of the photovoltaic system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic power generation, and in particular to an intelligent control method for a photovoltaic grid-connected inverter. Background Art

[0002] With the development of economy and society, solar energy has become one of the most promising new energy sources at home and abroad with its inexhaustible and environmentally friendly advantages. Photovoltaic grid-connected power generation is to connect the photovoltaic power generation system directly to the power grid, eliminating the bulky, expensive and difficult to maintain batteries. As one of the key equipment of the photovoltaic grid-connected power generation system, the performance of the grid-connected inverter is of great significance to improving the efficiency of photovoltaic power generation and reducing costs. The photovoltaic grid-connected inverter is the energy conversion link of the solar power generation system. The photovoltaic grid-connected inverter affects and determines whether the entire photovoltaic grid-connected system can operate stably, safely, reliably and efficiently.

[0003] At present, the control method of photovoltaic grid-connected inverter does not take into account the changes between the equipment operating parameters when tracking the maximum power point, resulting in low accuracy in tracking the maximum power point, and the output of the photovoltaic grid-connected inverter cannot be adjusted according to the actual operating conditions and cannot be optimized in real time, resulting in low efficiency of the photovoltaic system and energy efficiency loss. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent control method for a photovoltaic grid-connected inverter, which solves the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solution: an intelligent control method for a photovoltaic grid-connected inverter, comprising the following steps: System inspection: After the inverter is powered on, perform a self-check of the photovoltaic system to ensure that all components are working properly, measure the voltage, frequency and phase angle of the grid, and confirm that the grid status meets the grid connection conditions; Maximum power point tracking measures the output voltage and current of the photovoltaic array in the photovoltaic system in real time, uses the incremental algorithm to obtain the power increment ΔP(K) of the Kth iteration, and then uses the maximum power point tracking algorithm and the power increment ΔP(K) to obtain the maximum power point P of the Kth iteration. max (K); Grid-connected control: connect the inverter to the grid and synchronize it with the grid by controlling the inverter's output frequency, phase and voltage. During the synchronization process, gradually increase the inverter's output power until it is fully connected to the grid. Intelligent power regulation: After the inverter is connected to the grid, it monitors the voltage, current, phase and output power of the grid in real time, and adjusts the inverter output through the power optimization algorithm to make it close to the theoretical maximum power point, thereby improving system efficiency. Safety maintenance measures, set up overload protection, short circuit protection and over-temperature protection safety measures, and conduct regular system inspections and maintenance to ensure long-term stable operation.

[0006] Optionally, the incremental algorithm process is as follows: ;

[0007] Where ΔP(K) is the power increment at the Kth iteration; α is the incremental factor adjustment coefficient, with an initial value of 0.7; V in (K) Input voltage at the Kth iteration; V in (K-1) is the input voltage of the K-1th iteration; I in (K) Input current of the Kth iteration; The specific process is as follows: ΔP(K) can more accurately calculate the power increment by taking into account the changes in voltage difference and current, and gradually adjust the power to improve the accuracy of maximum power point tracking.

[0008] Optionally, the maximum power point tracking algorithm process is as follows:

[0009] Where P max (K) is the maximum power point of the Kth iteration; P max (K-1) Maximum power point of the K-1th iteration; ΔP(K) is the power increment at the Kth iteration; V in (K) Input voltage at the Kth iteration; V ref (K) reference voltage of the Kth iteration; β is the voltage difference influence coefficient; is a correction item; The specific process is as follows: By gradually updating the maximum power point in combination with ΔP(K), overshoot and stability problems caused by overcompensation can be avoided, making it more stable when tracking the maximum power point.

[0010] Optionally, the power optimization algorithm process is as follows: ;

[0011] Where ΔP opt (K) is the power optimization adjustment amount for the Kth iteration; β is the influence coefficient of the optimization adjustment; P max (K) is the maximum power point of the Kth iteration; P act (K) is the actual power output at the Kth iteration; γ is the voltage change influence coefficient; V in (K) is the output voltage of the Kth iteration; V in (K-1) is the output voltage of the K-1th iteration; is the voltage variation coefficient; set up The threshold Y is: ;

[0012] Where V max is the maximum voltage; V min is the minimum voltage; V nom is the rated voltage; ΔP is obtained by power optimization algorithm opt (K) to adjust the inverter output and, after multiple iterations, bring it close to the theoretical maximum power point, thereby improving system efficiency; when When it is greater than the threshold Y, α in the incremental algorithm changes, specifically: .

[0013] Optionally, in the power optimization algorithm, the iteration stops when the power increment change B is within a set range. When the power increment change B is less than 1%, the iteration stops. At this time, the system is close to the maximum power point. The calculation process of the power increment change B is as follows: ;

[0014] Where P is the incremental change in power; ΔP opt (K) is the power optimization adjustment amount for the Kth iteration; ΔP opt (K-1) is the power optimization adjustment amount for the K-1th iteration.

[0015] Optionally, the photovoltaic system self-check includes a basic status check, an indicator light check and a parameter display check. The basic status check includes confirming that the inverter is correctly connected to the power supply and the power indicator light is on. The indicator light check includes that after the inverter is powered on, the start indicator light should be always on, indicating that the inverter has been started. Check whether there is a fault indicator light. If the fault indicator light is on, it means that there is a fault in the inverter. The parameter display check is for various parameter displays after the inverter is powered on. The parameters include input voltage, battery status, and output power.

[0016] Optionally, the inverter is equipped with a wireless communication module, and the communication status of the inverter is checked through a mobile phone or other communication equipment, and the inverter uploads data to a monitoring platform through the wireless communication module for remote monitoring.

[0017] 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 device temperature in real time and setting a temperature alarm function to remind the operator of abnormal device temperature for subsequent processing.

[0018] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention comprehensively considers the changes in voltage difference and current through an incremental algorithm, can calculate the power increment more accurately, and gradually adjust the power, improve the accuracy of maximum power point tracking, and can adjust the power oscillation caused by voltage and current fluctuations through the incremental factor adjustment coefficient α, so that the photovoltaic system can operate more stably and improve the overall performance. The maximum power point is gradually updated through the maximum power point tracking algorithm combined with the power increment of the incremental algorithm, and the correction term is used to adjust the influence of the incremental algorithm result, so as to reduce the power oscillation caused by voltage and current fluctuations, so that the system can respond quickly to environmental changes. The above algorithms are interconnected and jointly improve the speed and accuracy of maximum power tracking.

[0019] 2. The present invention obtains the power optimization adjustment amount through the power optimization algorithm combined with the maximum power point tracking algorithm to adjust the inverter output, and after multiple iterations, makes it close to the theoretical maximum power point, thereby improving the working efficiency of the photovoltaic system. By introducing the voltage change threshold and the optimization adjustment amount influence coefficient β, it can quickly respond to voltage fluctuations. When the environment changes, it can quickly adjust and optimize, and achieve the effect of adjustment according to the actual operating conditions, ensuring that the photovoltaic system always operates at a position 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, so that the photovoltaic system can be adjusted only when the voltage changes significantly, avoiding frequent adjustments caused by small voltage changes, reducing system fluctuations, improving overall stability, and strengthening the connection strength between algorithms, so that they together constitute an intelligent control system for photovoltaic grid-connected inverters, ensuring the working efficiency of the photovoltaic system and avoiding energy efficiency loss. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] For example, see Figure 1 To the figure, this embodiment provides an intelligent control method for a photovoltaic grid-connected inverter, comprising the following steps: System inspection: After the inverter is powered on, perform a self-check of the photovoltaic system to ensure that all components are working properly, measure the voltage, frequency and phase angle of the grid, and confirm that the grid status meets the grid connection conditions; Maximum power point tracking measures the output voltage and current of the photovoltaic array in the photovoltaic system in real time, uses the incremental algorithm to obtain the power increment ΔP(K) of the Kth iteration, and then uses the maximum power point tracking algorithm and obtains the maximum power point P of the Kth iteration based on ΔP(K). max (K); Grid-connected 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. Intelligent power regulation: After the inverter is connected to the grid, it monitors the voltage, current, phase and output power of the grid in real time, and adjusts the inverter output through the power optimization algorithm to make it close to the theoretical maximum power point, thereby improving system efficiency. Safety maintenance measures, set up overload protection, short circuit protection and over-temperature protection safety measures, and conduct regular system inspections and maintenance to ensure long-term stable operation.

[0023] Short-circuit protection includes installing a fuse 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 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 processing.

[0024] In this embodiment, the system self-checks to ensure that all components are working properly, and measures the voltage, frequency and phase angle of the power grid in real time to confirm that the power grid status meets the grid-connected conditions, so as to promptly discover and solve problems and ensure that subsequent intelligent control of the photovoltaic grid-connected inverter can be carried out stably. The incremental algorithm is used to calculate the power increment in real time, and the maximum power point is updated based on this, which improves the accuracy of tracking the maximum power point and ensures that the photovoltaic system can operate close to the maximum power point. By accurately controlling the output frequency, phase and voltage of the inverter, the output power is gradually increased during the grid-connected process to ensure smooth grid connection and improve the stability of the grid-connected process. The power optimization algorithm is used for real-time monitoring, and the inverter output is adjusted according to the actual operating conditions to make it close to the theoretical maximum power point, so as to achieve real-time optimization and improve the overall performance and work efficiency of the photovoltaic system.

[0025] Furthermore, the incremental algorithm process is as follows: ;

[0026] Where ΔP(K) is the power increment at the Kth iteration; α is the incremental factor adjustment coefficient, with an initial value of 0.7; V in (K) Input voltage at the Kth iteration; V in (K-1) is the input voltage of the K-1th iteration; I in (K) Input current of the Kth iteration; Specifically, ΔP(K) can calculate the power increment more accurately by comprehensively considering the changes in voltage difference and current, improve the accuracy of maximum power point tracking by gradually adjusting the power, and adjust the power oscillation caused by voltage and current fluctuations through the increment factor adjustment coefficient α, making the photovoltaic system run more stably and improving the overall performance.

[0027] Furthermore, the maximum power point tracking algorithm process is as follows: ;

[0028] Where P max(K) is the maximum power point of the Kth iteration; P max (K-1) Maximum power point of the K-1th iteration; ΔP(K) is the power increment at the Kth iteration; V in (K) Input voltage at the Kth iteration; V ref (K) reference voltage of the Kth iteration; β is the voltage difference influence coefficient; is a correction term used to adjust the influence of ΔP(K); The specific process is as follows: By gradually updating the maximum power point in combination with ΔP(K), overshoot and stability problems caused by overcompensation can be avoided, making it more stable when tracking the maximum power point.

[0029] Specifically, through dynamic ΔP(K), power output fluctuations and system oscillations caused by over-adjustment are effectively reduced, stability is improved, and data in the photovoltaic system is monitored in real time, and the input voltage V of the Kth iteration is fully considered. in (K) and the reference voltage V of the Kth iteration ref (K) is calculated and the correction term is used Adjusting the influence of ΔP(K) reduces power oscillations caused by voltage and current fluctuations, allowing the system to respond quickly to environmental changes and improving the speed and accuracy of maximum power tracking.

[0030] Furthermore, the power optimization algorithm process is as follows: ;

[0031] Where ΔP opt (K) is the power optimization adjustment amount for the Kth iteration; β is the influence coefficient of the optimization adjustment; P max (K) is the maximum power point of the Kth iteration; P act (K) is the actual power output at the Kth iteration; γ is the voltage change influence coefficient; V in (K) is the output voltage of the Kth iteration; V in (K-1) is the output voltage of the K-1th iteration; is the voltage variation coefficient; set up The threshold Y is: ;

[0032] Where V max is the maximum voltage; V min is the minimum voltage; V nom is the rated voltage; Specifically, ΔP is obtained through the 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 the voltage change threshold and optimizing the adjustment amount influence coefficient β, it is able to quickly respond to voltage fluctuations. This increase in response speed helps the system to quickly adjust and optimize when the environment changes, achieving the effect of adjusting according to actual operating conditions and ensuring that the photovoltaic system always operates at a position close to the maximum power point.

[0033] when When it is greater than the threshold Y, α in the incremental algorithm changes, specifically: ;

[0034] Specifically, by adjusting α in the incremental algorithm in real time according to the voltage change coefficient, the photovoltaic system can be adjusted only when the voltage changes significantly, avoiding unnecessary frequent adjustments, making the adjustment process more efficient and accurate, reducing power fluctuations caused by excessive adjustments, and reducing the energy consumption of the system. 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.

[0035] Furthermore, in the power optimization algorithm, the iteration stops when the power increment change B is within the set range. When the power increment change B is less than 1%, the iteration stops. At this time, the system is close to the maximum power point. The calculation process of the power increment change B is as follows: ;

[0036] Where P is the incremental change in power; ΔP opt (K) is the power optimization adjustment amount for the Kth iteration; ΔP opt (K-1) is the power optimization adjustment amount for the K-1th iteration.

[0037] Specifically, by setting the range of the power increment change B, the iteration is limited to avoid infinite iterations that may cause errors in the system computing equipment, and the iteration is stopped when the power increment change B is less than 1%. At this time, the system is close to the maximum power point and there is no need for the next iteration. At this time, the incremental algorithm, maximum power point tracking algorithm and power optimization algorithm are all stopped, thereby saving computing time and improving the working efficiency of the photovoltaic system.

[0038] Furthermore, the PV system self-test includes basic status check, indicator light check and parameter display check. The basic status check includes confirming that the inverter has been correctly connected to the power supply and the power indicator light is on. The indicator light check includes that after the inverter is powered on, the start indicator light should be always on, indicating that the inverter has been started. Check whether there is a fault indicator light. If the fault indicator light is on, it means that there is a fault in the inverter. For the inverter with a digital screen, the parameter display check displays various parameters after power-on. The parameters include input voltage, battery status, and output power.

[0039] Specifically, through the PV system self-check, the inverter can conduct a comprehensive check of the internal hardware and software status at the initial startup to ensure the normal operation of each component, avoid system instability or shutdown due to equipment failure or configuration errors, improve the reliability of the PV system, and ensure that the inverter can operate stably for a long time.

[0040] Furthermore, 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 processing.

[0041] Specifically, safety maintenance measures ensure that the photovoltaic system can automatically disconnect or limit current under abnormal circumstances, prevent equipment damage or system failure, and improve overall reliability. By preventing overload and overtemperature, it can reduce equipment stress and wear and extend the service life of the equipment. By effectively controlling power and heat, it reduces energy waste caused by failures or overloads and improves the energy efficiency of the system. Safety maintenance measures reduce safety hazards caused by electrical failures and ensure the safety of operators and the environment around the equipment.

[0042] Embodiment 2: Based on the above embodiment, the inverter is equipped with a wireless communication module, and the communication status of the inverter can be checked through a mobile phone or other communication equipment. The inverter can upload data to a monitoring platform through the wireless communication module for remote monitoring.

[0043] By equipping the inverter with a wireless communication module, the inverter has remote monitoring and management functions. The inverter operating status can be transmitted to the remote monitoring center through the network, so that the operation and maintenance personnel can understand the status of the inverter at any time and any place, and respond to fault alarms in time, thereby improving the flexibility of the photovoltaic system.

[0044] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent control method for a photovoltaic grid-connected inverter, characterized in that: The following steps are involved: Step S1: System check: After the inverter is powered on, the photovoltaic system self-checks 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, real-time measurement of the output voltage and current of the photovoltaic array in the photovoltaic system, using the incremental algorithm to obtain the power increment ΔP(K) of the Kth iteration, and using the maximum power point tracking algorithm and the power increment ΔP(K) to obtain the maximum power point P of the Kth iteration. max (K); Step S3: Grid connection control, connecting the inverter to the grid, controlling the output frequency, phase and voltage of the inverter to synchronize it with the grid, and gradually increasing the output power of the inverter until it is fully connected to the grid; Step S4: intelligent power regulation. After the inverter is connected to the grid, the inverter monitors the voltage, current, phase and output power of the grid in real time, and uses the power optimization algorithm to adjust the inverter output to make it close to the maximum power point. Step S5: Safety maintenance measures, setting overload protection, short circuit protection and over-temperature protection safety measures, and performing regular system inspection and maintenance.

2. The intelligent control method of photovoltaic grid-connected inverter according to claim 1, characterized in that: The incremental algorithm formula is as follows: ； Where ΔP(K) is the power increment of the Kth iteration; α is the incremental factor adjustment coefficient, and its initial value is 0.7; V in (K) is the input voltage of the Kth iteration; V in (K-1) is the input voltage of the K-1th iteration; I in (K) is the input current of the Kth iteration; ΔP(K) calculates the power increment by comprehensively considering the changes in voltage difference and current, and gradually adjusts the power to improve the accuracy of maximum power point tracking.

3. The intelligent control method of photovoltaic grid-connected inverter according to claim 2, characterized in that: The maximum power point tracking algorithm formula is as follows: ； Where P max (K) is the maximum power point of the Kth iteration; P max (K-1) is the maximum power point of the K-1th iteration; ΔP(K) is the power increment of the Kth iteration; V in (K) is the input voltage of the Kth iteration; V ref (K) is the reference voltage of the Kth iteration; β is the voltage difference influence coefficient; is the correction item; By gradually updating the maximum power point in combination with ΔP(K), overshoot and stability problems caused by overcompensation can be avoided, making it more stable when tracking the maximum power point.

4. The intelligent control method of photovoltaic grid-connected inverter according to claim 3, characterized in that: The power optimization algorithm formula is as follows: ； Where ΔP opt (K) is the power optimization adjustment value of the Kth iteration; β is the influence coefficient of the optimization adjustment; P max (K) is the maximum power point of the Kth iteration; P act (K) is the actual power output of the Kth iteration; γ is the voltage change influence coefficient; V in (K) is the output voltage of the Kth iteration; V in (K-1) is the output voltage of the K-1th iteration; is the voltage variation coefficient; set up The threshold Y is: ； Where V max is the maximum voltage; V min is the minimum voltage; V nom is the rated voltage; ΔP is obtained by power optimization algorithm opt (K) to adjust the inverter output and bring it close to the theoretical maximum power point after multiple iterations; when When it is greater than the threshold value Y, the change formula of the incremental factor adjustment coefficient α in the incremental algorithm is as follows: 。 5. The intelligent control method of photovoltaic grid-connected inverter according to claim 4, characterized in that: The iteration in the power optimization algorithm stops when the power increment change B is less than 1%. At this time, the system is close to the maximum power point. The specific formula of the power increment change B is as follows: ； Where P is the power increment change; ΔP opt (K) is the power optimization adjustment value of the Kth iteration; ΔP opt (K-1) is the power optimization adjustment amount of the K-1th iteration.

6. The intelligent control method of photovoltaic grid-connected inverter according to claim 1, characterized in that: The photovoltaic system self-check includes basic status check, indicator light check and parameter display check; The basic status check includes confirming that the inverter has been correctly connected to the power supply and the power indicator light is on. The indicator light check includes that after the inverter is powered on, the start indicator light should be always on, indicating that the inverter has started. Check whether there is a fault indicator light. If the fault indicator light is on, it means that there is a fault in the inverter. The parameter display check is for the display of various parameters after the inverter is powered on; Parameters include input voltage, battery status, and output power.

7. The intelligent control method of photovoltaic grid-connected inverter according to claim 1, characterized in that: The inverter is equipped with a wireless communication module, and the communication status of the inverter can be checked through a mobile phone or other communication equipment, and the inverter uploads data to the monitoring platform through the wireless communication module.

8. The intelligent control method of photovoltaic grid-connected inverter according to claim 1, characterized in that: 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.

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