Island detection method and system based on combination of particle swarm optimization and improved AFDPF algorithm

Abstract

The invention relates to the technical field of island detection, and discloses an island detection method and system based on the combination of a particle swarm algorithm and an improved AFDPF algorithm, and the method comprises the steps: adding a frequency disturbance initial value at an inverter control side, and detecting the PCC point frequency; judging whether the PCC point frequency exceeds a power grid standard operation specified range or not, if not, returning to the previous step to add disturbance again, and if yes, performing the next step; detecting active power and reactive power of a load, updating a positive feedback coefficient in real time through a particle swarm algorithm, and substituting the improved AFDPF algorithm to update a disturbance direction; and judging whether an islanding effect occurs or not according to the PCC point frequency, and generating a solution. The particle swarm optimization algorithm is used for improving the positive feedback coefficient h in real time, meanwhile, the AFDPF algorithm is optimized, the detection accuracy is improved, the detection blind area is greatly reduced, the detection time is greatly shortened, and meanwhile harmonic waves disturbed and injected into a power grid are restrained.

Description

Technical Field

[0001] The present invention relates to the technical field of island detection, and in particular to an island detection method and system based on the combination of a particle swarm algorithm and an improved AFDPF algorithm. Background Art

[0002] When a power grid fails due to human or natural factors, the grid may stop supplying power to the load, but the photovoltaic grid-connected system still maintains power transmission to the load, and a self-sufficient power supply island that cannot be controlled by the grid company is generated. This is the island effect. When the grid and the photovoltaic grid-connected system supply power together, the grid often has operational errors or needs maintenance, which will cause the load to stop obtaining power from the grid for a short time. Therefore, the island effect often occurs in the system. The safe and stable operation of the power system will be seriously threatened. Once the island effect occurs, the grid-connected inverter must be cut off quickly and accurately. Therefore, it is an urgent problem to detect the island effect quickly and accurately.

[0003] Active method and passive method are the two main island detection methods at present. Passive island detection method: monitor whether the output of the inverter exceeds the standard range according to the grid connection standard. This method is simple and easy to implement. However, if the local load power is equal to the inverter output power, this method fails; Active island detection method: add a small disturbance on the inverter control side to monitor whether the output of the inverter exceeds the standard range. This method has high accuracy and a small blind area, but there is a problem of complex control, and the quality of power obtained by the load will decrease.

[0004] Among the active island detection methods, the positive feedback active frequency shift method (AFDPF) is a simple and effective method that adds a moderate frequency offset to the control system. In this way, the inverter current with the offset frequency as a reference will be disturbed. The main problem of AFDPF is that with the change of load and frequency, in order to ensure a small blind area, the positive feedback coefficient h needs to be reset each time. And when the load is capacitive, there may be a problem of mutual compensation between the lag effect of the impedance angle and the leading effect of the offset frequency. The island effect is difficult to detect, which has certain problems. Summary of the invention

[0005] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0006] In view of the above existing problems, the present invention is proposed. Therefore, the present invention provides an islanding detection method based on a particle swarm algorithm and an improved AFDPF algorithm to solve the islanding effect problem when the main grid is unplanned disconnected and the photovoltaic grid-connected power generation system still supplies power to the load.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] In a first aspect, the present invention provides an island detection method based on a combination of a particle swarm algorithm and an improved AFDPF algorithm, comprising:

[0009] Add the initial value of frequency disturbance on the inverter control side and detect the PCC point frequency;

[0010] Determine whether the frequency of the PCC point exceeds the range specified by the standard operation of the power grid. If it does not exceed the range, return to the previous step and re-add the disturbance. If it exceeds the range, proceed to the next step.

[0011] Detect the active power and reactive power of the load, and based on the active power, reactive power and PCC point frequency of the load, update the positive feedback coefficient in real time through the particle swarm algorithm, and substitute it into the improved AFDPF algorithm to update the disturbance direction;

[0012] It is determined whether an islanding effect occurs according to the PCC point frequency, and a solution is generated.

[0013] As a preferred solution of the island detection method based on the combination of particle swarm algorithm and improved AFDPF algorithm described in the present invention, wherein: adding the initial value of frequency disturbance on the inverter control side and detecting the PCC point frequency includes:

[0014] Add the initial value of frequency disturbance af0 on the inverter control side as a key factor to determine the frequency change when the islanding effect occurs;

[0015] The PCC point frequency is detected in real time, and the frequency detection value and frequency change trend are recorded.

[0016] As a preferred solution of the island detection method based on the combination of particle swarm algorithm and improved AFDPF algorithm described in the present invention, the frequency of the PCC point exceeds the range specified by the grid standard operation, including:

[0017] Preset the frequency operating range, and compare the value of the PCC point frequency detected in real time with the value of the frequency operating range;

[0018] If the frequency operating range is not exceeded, return to the previous step, reset and add the initial value of the frequency disturbance;

[0019] If it exceeds the frequency operating range, proceed to the next step to detect the active power and reactive power of the load.

[0020] As a preferred solution of the island detection method based on the combination of particle swarm algorithm and improved AFDPF algorithm described in the present invention, the positive feedback coefficient is updated in real time by the particle swarm algorithm and substituted into the improved AFDPF algorithm, and the disturbance direction is updated including:

[0021] When the PCC point frequency exceeds the frequency operating range, the active power and reactive power values ​​of the load are detected as the quality factor of the load;

[0022] The detection blind area is improved by particle swarm algorithm. The load quality factor and PCC point frequency are input into the blind area formula. The positive feedback coefficient h and the disturbance action direction are used as chromosome genes to solve the positive feedback coefficient h that reduces the blind area range and keeps the harmonics injected into the power grid within the specified range.

[0023] The positive feedback coefficient h is input into the improved AFDPF algorithm, and the value of the sign function is determined according to the frequency offset value to obtain the disturbance amount applied by the control side.

[0024] As a preferred solution of the island detection method based on the combination of particle swarm algorithm and improved AFDPF algorithm described in the present invention, the blind area formula is expressed as:

[0025]

[0026] Among them, Q f0 represents the load quality factor, Δω represents the angular velocity change, af0 represents the initial value of the frequency disturbance, ω0 represents the initial value of the angular velocity, and h represents the positive feedback coefficient.

[0027] As a preferred solution of the island detection method based on the combination of particle swarm algorithm and improved AFDPF algorithm described in the present invention, the improved AFDPF algorithm is expressed as:

[0028] af=af0+h|f-f0|+|h(f-f0)| 3 sign(f-f0)

[0029]

[0030] Among them, f represents the PCC point frequency, and f0 represents the rated frequency.

[0031] As a preferred solution of the island detection method based on the combination of particle swarm algorithm and improved AFDPF algorithm described in the present invention, judging whether an island effect occurs according to the PCC point frequency includes:

[0032] Determine whether the PCC point frequency exceeds the frequency operating range, and if it does not exceed the frequency operating range, return to the first step to re-add the initial value of the frequency disturbance and perform a finite loop;

[0033] If the frequency exceeds the operating range, it is determined that an islanding effect has occurred and the inverter is disconnected.

[0034] In a second aspect, the present invention provides an island detection system based on a combination of a particle swarm algorithm and an improved AFDPF algorithm, comprising:

[0035] A processing module, used for adding an initial value of frequency disturbance on the inverter control side and detecting the PCC point frequency;

[0036] A judgment module is used to judge whether the frequency of the PCC point exceeds the range specified by the standard operation of the power grid. If it does not exceed the range, return to the previous step to re-add the disturbance; if it exceeds the range, proceed to the next step;

[0037] An updating module is used to detect the active power and reactive power of the load, and based on the active power, reactive power and PCC point frequency of the load, update the positive feedback coefficient in real time through a particle swarm algorithm, and substitute it into the improved AFDPF algorithm to update the disturbance direction;

[0038] The output module is used to determine whether an islanding effect occurs according to the PCC point frequency and generate a solution.

[0039] In a third aspect, the present invention provides an electronic device, comprising:

[0040] Memory and processor;

[0041] The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the island detection method based on the combination of particle swarm algorithm and improved AFDPF algorithm are implemented.

[0042] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the island detection method based on the combination of a particle swarm algorithm and an improved AFDPF algorithm.

[0043] Compared with the prior art, the present invention has the following beneficial effects: the present invention uses a particle swarm algorithm to improve the positive feedback coefficient h in real time, and optimizes the AFDPF algorithm at the same time, so that the detection accuracy is improved, the detection blind area and the detection time are greatly reduced, and the harmonics of the disturbance injection into the power grid are suppressed. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0045] Figure 1 It is a schematic diagram of the overall process of an island detection method based on a combination of a particle swarm algorithm and an improved AFDPF algorithm according to an embodiment of the present invention;

[0046] Figure 2 The figure is a schematic diagram of a specific process of an island detection method based on a combination of a particle swarm algorithm and an improved AFDPF algorithm according to an embodiment of the present invention. DETAILED DESCRIPTION

[0047] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0048] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0049] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0050] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0051] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0052] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0053] Reference Figure 1-Figure 2 , which is an embodiment of the present invention, provides an island detection method based on a combination of a particle swarm algorithm and an improved AFDPF algorithm, comprising:

[0054] S101, adding an initial value of frequency disturbance on the inverter control side and detecting the PCC point frequency;

[0055] S102, determining whether the frequency of the PCC point exceeds the range specified by the grid standard operation, if not, returning to the previous step to re-add the disturbance, if not, proceeding to the next step;

[0056] S103, detecting the active power and reactive power of the load, and based on the active power, reactive power and PCC point frequency of the load, updating the positive feedback coefficient in real time through the particle swarm algorithm, and substituting it into the improved AFDPF algorithm to update the disturbance direction;

[0057] S104, judging whether an islanding effect occurs according to the PCC point frequency, and generating a solution.

[0058] It should be noted that this embodiment adds a moderate frequency offset to the control system, and the inverter current with the offset frequency as a reference will be disturbed. When the power grid normally supplies power to the load, the grid voltage has a clamping effect on the PCC point. Even if a disturbance offset is added to the control, the frequency of the PCC point will not change. However, when the main grid unexpectedly interrupts the power supply to the load, the clamping effect of the main grid disappears, and the voltage and frequency of the PCC point will be displaced due to the current with frequency offset output by the inverter. The addition of the positive feedback coefficient h causes the system frequency to quickly exceed the set value of the detection, and the detection time is significantly shortened.

[0059] Based on the improved AFDPF algorithm, a moderate frequency offset is added to the control system, and the inverter current with the offset frequency as a reference will be disturbed. Then the particle swarm algorithm is used to improve the positive feedback coefficient h in real time, reduce the detection blind area, suppress the harmonics injected into the power grid, and realize the rapid detection of the islanding effect.

[0060] In a preferred implementation, adding an initial value of frequency disturbance on the inverter control side and detecting the PCC point frequency includes:

[0061] Add the initial value of frequency disturbance af0 on the inverter control side as a key factor to determine the frequency change when the islanding effect occurs;

[0062] Detect PCC point frequency in real time, and record frequency detection value and frequency change trend.

[0063] It should be noted that when the main power grid supplies power to the load normally, the frequency fluctuates within the normal range. At this time, directly optimizing and adding the positive feedback coefficient h may result in excessive disturbance, which in turn causes the detection device to malfunction. Therefore, a smaller initial disturbance value is given first. If an island occurs, the disturbance can accumulate rapidly, causing the frequency to exceed the normal range, thereby executing the subsequent steps.

[0064] The frequency of the PCC point is detected because when a moderate frequency offset is added to the control system, the inverter current with the offset frequency as a reference will be disturbed, and the frequency will show a trend of continuous change. When the power grid supplies power to the load normally, the grid voltage has a clamping effect on the PCC point. Even if a disturbance offset is added to the control, the frequency of the PCC point will not change. However, when the main grid unexpectedly interrupts the power supply to the load, the clamping effect of the main grid disappears, and the voltage and frequency of the PCC point will be displaced due to the current with frequency offset output by the inverter, and the frequency offset will gradually increase with time. Therefore, the frequency of the PCC point can be detected to determine whether to execute the next step.

[0065] In a preferred embodiment, the frequency at the PCC point exceeds the range specified by the grid standard operation, including:

[0066] Preset the frequency operating range and compare the real-time detected PCC point frequency value with the value of the frequency operating range;

[0067] If the frequency operating range is not exceeded, return to the previous step, reset and add the initial value of the frequency disturbance;

[0068] If it exceeds the frequency operating range, proceed to the next step to detect the active power and reactive power of the load.

[0069] It should be noted that only when the frequency of the PCC point exceeds the normal range, the island detection method will be used to detect whether the island effect has occurred. Otherwise, it is judged that the island effect has not occurred.

[0070] In a preferred embodiment, the positive feedback coefficient is updated in real time by a particle swarm algorithm and substituted into the improved AFDPF algorithm. The updating disturbance direction includes:

[0071] When the PCC point frequency exceeds the frequency operating range, the active power and reactive power values ​​of the load are detected as the quality factor of the load;

[0072] The detection blind area is improved by particle swarm algorithm. The load quality factor and PCC point frequency are input into the blind area formula. The positive feedback coefficient h and the disturbance action direction are used as chromosome genes to solve the positive feedback coefficient h that reduces the blind area range and keeps the harmonics injected into the power grid within the specified range.

[0073] The positive feedback coefficient h is input into the improved AFDPF algorithm, and the value of the sign function is determined according to the frequency offset value to obtain the disturbance applied by the control side.

[0074] It should be noted that since the detection blind area is related to the quality factor of the load, in order to reduce the real-time blind area, the active power and reactive power of the load must be known.

[0075] When the local load is connected in parallel with RCL and the AFDPF algorithm is used to detect the islanding effect, there will be a detection blind area. If the load is capacitive, the lag effect of the impedance angle and the lead effect of the offset frequency will compensate each other, making it impossible to detect the island effect.

[0076] In a preferred embodiment, the blind area formula is expressed as:

[0077]

[0078] Among them, Q f0 represents the load quality factor, Δω represents the angular velocity change, af0 represents the initial value of the frequency disturbance, ω0 represents the initial value of the angular velocity, and h represents the positive feedback coefficient.

[0079] In order to reduce the blind area, the positive feedback coefficient h and the disturbance direction are updated in real time through the particle swarm algorithm according to the active power, reactive power and PCC point frequency of the load.

[0080] The obtained positive feedback coefficient h is brought into the improved AFDPF algorithm to obtain the frequency disturbance amount that should be applied on the control side, and to detect whether the PCC point frequency exceeds the specified value to determine whether an islanding effect occurs.

[0081] In a preferred embodiment, the improved AFDPF algorithm is expressed as:

[0082] af=af0+h|f-f0|+|h(f-f0)| 3 sign(f-f0)

[0083]

[0084] Among them, f represents the PCC point frequency, and f0 represents the rated frequency.

[0085] It should be noted that when the AFDPF detects the islanding effect, for the fixed positive feedback coefficient h, when the load changes, in order to ensure that there is no blind spot, h must be reset. The present invention introduces a particle swarm algorithm to update h in real time, which can ensure that when the load and frequency change, the detection blind area always maintains a small value, or even no blind area, which greatly improves the detection accuracy and success rate. The improvement of the detection success rate will also reduce the action time of the disturbance, thereby reducing the harmonics injected into the power grid by the disturbance and improving the power quality.

[0086] In the improved AFDPF algorithm, |h(f-f0)| 3 sign(f-f0) can avoid the situation where the lag effect of the impedance angle and the lead effect of the offset frequency compensate for each other, thereby improving the success rate of detection.

[0087] When the power grid is working normally, since f-f0≈0, the disturbance is approximately the initial value and is very small, and the harmonics injected into the power grid are very small. When the islanding effect occurs, the particle swarm optimization algorithm is used to update the positive feedback coefficient h in real time, which effectively suppresses the further increase of harmonics injected into the power grid by the disturbance.

[0088] In a preferred embodiment, judging whether an islanding effect occurs according to the PCC point frequency includes:

[0089] Determine whether the PCC point frequency exceeds the frequency operating range. If it does not exceed the frequency operating range, return to the first step and re-add the initial value of the frequency disturbance to perform a finite cycle;

[0090] If the frequency exceeds the operating range, it is determined that an islanding effect has occurred and the inverter is disconnected.

[0091] It should be noted that the disturbance is superimposed with the offset, and the blind area under this load condition is greatly reduced, the time when the PCC point frequency exceeds the threshold set by the protection is greatly reduced, and the detection accuracy is improved. If the system has an island effect, it must be determined under a limited number of cycles.

[0092] The present invention uses a particle swarm algorithm to improve the positive feedback coefficient h in real time, and optimizes the AFDPF algorithm at the same time, so that the detection accuracy is improved, the detection blind area and the detection time are greatly reduced, and the harmonics of the disturbance injection into the power grid are suppressed.

[0093] The above is a schematic scheme of an island detection method based on a combination of a particle swarm algorithm and an improved AFDPF algorithm in this embodiment. It should be noted that the technical solution of the island detection system based on a combination of a particle swarm algorithm and an improved AFDPF algorithm and the technical solution of the island detection method based on a combination of a particle swarm algorithm and an improved AFDPF algorithm belong to the same concept. The details of the technical solution of the island detection system based on a combination of a particle swarm algorithm and an improved AFDPF algorithm in this embodiment that are not described in detail can all be referred to the description of the technical solution of the island detection method based on a combination of a particle swarm algorithm and an improved AFDPF algorithm.

[0094] The island detection system based on the particle swarm algorithm and the improved AFDPF algorithm in this embodiment includes:

[0095] A processing module, used for adding an initial value of frequency disturbance on the inverter control side and detecting the PCC point frequency;

[0096] The judgment module is used to judge whether the frequency of the PCC point exceeds the range specified by the grid standard operation. If it does not exceed the range, it returns to the previous step to re-add the disturbance. If it exceeds the range, it proceeds to the next step;

[0097] The update module is used to detect the active power and reactive power of the load. Based on the active power, reactive power and PCC point frequency of the load, the positive feedback coefficient is updated in real time through the particle swarm algorithm, and the improved AFDPF algorithm is substituted to update the disturbance direction.

[0098] The output module is used to determine whether the islanding effect occurs based on the PCC point frequency and generate a solution.

[0099] This embodiment further provides an electronic device, which is applicable to the case of island detection based on the combination of particle swarm algorithm and improved AFDPF algorithm, including:

[0100] Memory and processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the island detection method based on the combination of particle swarm algorithm and improved AFDPF algorithm as proposed in the above embodiment.

[0101] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the island detection method based on the combination of a particle swarm algorithm and an improved AFDPF algorithm as proposed in the above embodiment is implemented.

[0102] The storage medium proposed in this embodiment and the island detection method based on the combination of particle swarm algorithm and improved AFDPF algorithm proposed in the above embodiment belong to the same inventive concept. The technical details not described in detail in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0103] Through the above description of the implementation mode, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course can also be implemented by hardware, but in many cases the former is a better implementation mode. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ReadOnly, Memory, ROM), random access memory (RandomAccess Memory, RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform the methods of various embodiments of the present invention.

[0104] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An island detection method based on a combination of a particle swarm algorithm and an improved AFDPF algorithm, characterized in that: include: Add the initial value of frequency disturbance on the inverter control side and detect the PCC point frequency; Determine whether the frequency of the PCC point exceeds the range specified by the standard operation of the power grid. If it does not exceed the range, return to the previous step and re-add the disturbance. If it exceeds the range, proceed to the next step. Detect the active power and reactive power of the load, and based on the active power, reactive power and PCC point frequency of the load, update the positive feedback coefficient in real time through the particle swarm algorithm, and substitute it into the improved AFDPF algorithm to update the disturbance direction; It is determined whether an islanding effect occurs according to the PCC point frequency, and a solution is generated.

2. The island detection method based on the combination of particle swarm algorithm and improved AFDPF algorithm as claimed in claim 1, characterized in that: Adding the initial value of frequency disturbance on the inverter control side and detecting the PCC point frequency includes: Add the initial value of frequency disturbance af0 on the inverter control side as a key factor to determine the frequency change when the islanding effect occurs; The PCC point frequency is detected in real time, and the frequency detection value and frequency change trend are recorded.

3. The island detection method based on the combination of particle swarm algorithm and improved AFDPF algorithm as claimed in claim 2, characterized in that: The range based on the PCC point frequency exceeding the standard operation range of the power grid includes: Preset the frequency operating range, and compare the value of the PCC point frequency detected in real time with the value of the frequency operating range; If the frequency operating range is not exceeded, return to the previous step, reset and add the initial value of the frequency disturbance; If it exceeds the frequency operating range, proceed to the next step to detect the active power and reactive power of the load.

4. The island detection method based on the combination of particle swarm algorithm and improved AFDPF algorithm as claimed in claim 3 is characterized in that: The positive feedback coefficient is updated in real time through the particle swarm algorithm and substituted into the improved AFDPF algorithm. The updated disturbance direction includes: When the PCC point frequency exceeds the frequency operating range, the active power and reactive power values ​​of the load are detected as the quality factor of the load; The detection blind area is improved by particle swarm algorithm. The load quality factor and PCC point frequency are input into the blind area formula. The positive feedback coefficient h and the disturbance action direction are used as chromosome genes to solve the positive feedback coefficient h that reduces the blind area range and keeps the harmonics injected into the power grid within the specified range. The positive feedback coefficient h is input into the improved AFDPF algorithm, and the value of the sign function is determined according to the frequency offset value to obtain the disturbance amount applied by the control side.

5. The island detection method based on the combination of particle swarm algorithm and improved AFDPF algorithm as claimed in claim 4, characterized in that: The blind area formula is expressed as: Among them, Q f0 represents the load quality factor, Δω represents the angular velocity change, af0 represents the initial value of the frequency disturbance, ω0 represents the initial value of the angular velocity, and h represents the positive feedback coefficient.

6. The island detection method based on the combination of particle swarm algorithm and improved AFDPF algorithm as claimed in claim 5, characterized in that: The improved AFDPF algorithm is expressed as: af=af0+h|f-f0|+|h(f-f0)| 3 sign(f-f0) Among them, f represents the PCC point frequency, and f0 represents the rated frequency.

7. The island detection method based on the combination of particle swarm algorithm and improved AFDPF algorithm as described in any one of claims 4 to 6, characterized in that: Judging whether an islanding effect occurs according to the PCC point frequency includes: Determine whether the PCC point frequency exceeds the frequency operating range, and if it does not exceed the frequency operating range, return to the first step to re-add the initial value of the frequency disturbance and perform a finite loop; If the frequency exceeds the operating range, it is determined that an islanding effect has occurred and the inverter is disconnected.

8. An island detection system based on a combination of a particle swarm algorithm and an improved AFDPF algorithm, characterized in that: include: A processing module, used for adding an initial value of frequency disturbance on the inverter control side and detecting the PCC point frequency; A judgment module is used to judge whether the frequency of the PCC point exceeds the range specified by the standard operation of the power grid. If it does not exceed the range, return to the previous step to re-add the disturbance; if it exceeds the range, proceed to the next step; An updating module is used to detect the active power and reactive power of the load, and based on the active power, reactive power and PCC point frequency of the load, update the positive feedback coefficient in real time through a particle swarm algorithm, and substitute it into the improved AFDPF algorithm to update the disturbance direction; The output module is used to determine whether an islanding effect occurs according to the PCC point frequency and generate a solution.

9. An electronic device, characterized in that: include: Memory and processor; The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the island detection method based on the combination of particle swarm algorithm and improved AFDPF algorithm as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: It stores computer executable instructions, which, when executed by a processor, can implement the steps of the island detection method based on the combination of a particle swarm algorithm and an improved AFDPF algorithm as described in any one of claims 1 to 7.

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