A kind of distributed photovoltaic power generation unit measuring and controlling device and method

Abstract

The application relates to the photovoltaic power generation measurement and control technical field, in particular to a kind of distributed photovoltaic power generation unit's measurement and control device and method, the method comprises: using photovoltaic grid-connected point in regulation and control period window grid-connected point voltage time series data, the voltage variation rate of each sampling time is calculated, and then the voltage high-frequency fluctuation of high-frequency detail component is calculated;Extract abnormal peak point, through the number proportion and distribution density of abnormal peak point, combined with voltage high-frequency fluctuation, obtain voltage sudden abnormality degree, combined with the average distribution level of voltage effective value of grid-connected point voltage in regulation and control period window, and then the reactive power regulation power of photovoltaic inverter in each regulation and control period window is obtained.The application can accurately adjust the reactive power of photovoltaic inverter, effectively and quickly suppress the voltage fluctuation at photovoltaic grid-connected point, and ensure the stability of power grid operation in power system.

Description

Technical Field

[0001] This application relates to the field of photovoltaic power generation measurement and control technology, specifically to a measurement and control device and method for a distributed photovoltaic power generation unit. Background Technology

[0002] Because distributed photovoltaic (PV) power generation is intermittent and random, the integration of large-scale distributed PV units into the power system can disrupt grid power balance, causing rapid voltage fluctuations at the PV grid connection point. These fluctuations can even exceed the response and regulation capabilities of voltage regulators, severely impacting grid stability. Therefore, to ensure grid stability, monitoring and control devices are typically installed at the PV grid connection point. These devices monitor voltage data at the connection point and adjust the reactive power output of the PV inverters based on the monitoring results. This allows for rapid suppression of voltage fluctuations at the grid connection point, ensuring grid stability.

[0003] Because photovoltaic (PV) inverters have adjustable active and reactive power, to address the issue of unstable voltage fluctuations at the PV grid connection point, a monitoring and control device is used to monitor the voltage data at the PV grid connection point. The reactive power of the PV inverter is dynamically adjusted based on changes in voltage deviation at the PV grid connection point, thereby adjusting the reactive power output of the PV inverter and quickly suppressing voltage fluctuations at the PV grid connection point. Currently, existing dynamic reactive power adjustment methods based on voltage deviation at the PV grid connection point are suitable for compensating reactive power under steady-state voltage deviation conditions. However, the intermittent and random nature of distributed PV power generation can cause sudden voltage fluctuations. Existing technologies treat voltage deviation changes as a single factor for dynamic adjustment of the PV inverter's reactive power, ignoring sudden voltage fluctuations at the PV grid connection point. This makes it difficult to accurately and dynamically adjust the reactive power of the PV inverter, thus failing to effectively and quickly suppress voltage fluctuations at the PV grid connection point. Summary of the Invention

[0004] To address the aforementioned technical problems, the purpose of this application is to provide a measurement and control device and method for a distributed photovoltaic power generation unit, the specific technical solution of which is as follows:

[0005] This application provides a measurement and control method for a distributed photovoltaic power generation unit, including the following steps:

[0006] Each control cycle window is set up, and the voltage change rate at each sampling moment is calculated using the time-series data of the grid-connected point voltage within the control cycle window. Anomalies in the high-frequency detail components of the photovoltaic grid-connected point voltage change rate are analyzed to obtain the high-frequency voltage fluctuations of the high-frequency detail components. Abnormal peaks are extracted using the fluctuations in the peak voltage change rate of the high-frequency detail components. The voltage burst anomaly degree of each control cycle window is obtained by combining the proportion and density of abnormal peaks with the high-frequency voltage fluctuations. Furthermore, the reactive power regulation of the photovoltaic inverter within each control cycle window is obtained by combining the average distribution level of the effective voltage value of the grid-connected point voltage within the control cycle window.

[0007] Preferably, the difference between the grid connection point voltage at each sampling time and the previous sampling time is calculated, and the ratio of this difference to the absolute value of the grid connection point voltage at the previous sampling time is used as the voltage change rate at each sampling time.

[0008] Preferably, the voltage change rates at all sampling times within the control window are arranged in an inter-order manner to form a voltage change rate sequence. Discrete wavelet transform is used to extract the high-frequency detail components of each decomposition layer of the voltage change rate sequence. The multiple elements that are closest to each element in the high-frequency detail component are recorded as the nearest neighbors of each element in the high-frequency detail component. The vector formed by the distance between each element and its nearest neighbors according to the sorting method of the nearest neighbors in the high-frequency detail component is used as the voltage feature distance vector of each element.

[0009] Preferably, the standard deviation of all elements within the voltage characteristic distance vector of each element in the high-frequency detail component is calculated, the distance between each element in the high-frequency detail component and the voltage characteristic distance vector of its predecessor is calculated, and the mean of the product of the standard deviation and the distance of all elements in the high-frequency detail component is taken as the voltage high-frequency fluctuation of the high-frequency detail component.

[0010] Preferably, all peak points in the high-frequency detail components are extracted, and the average standard deviation of the voltage characteristic distance vector of each peak point is calculated as the screening threshold. Peak points with standard deviations greater than the screening threshold are regarded as abnormal spikes.

[0011] Preferably, the voltage burst anomaly degree of each control cycle window The formula for obtaining the relation is: In the formula, The number of high-frequency detail components. The peak percentage of the s-th high-frequency detail component is denoted as . The first proportion of the s-th high-frequency detail component. Let be the voltage high-frequency fluctuation of the s-th high-frequency detail component. To avoid extremely small positive numbers with a denominator of zero.

[0012] Preferably, the ratio of the number of all abnormal peaks in the high-frequency detail component to the total number of all peaks in the high-frequency detail component is used as the peak ratio of the high-frequency detail component.

[0013] Preferably, the positional difference between two adjacent abnormal peaks in the high-frequency detail component is calculated, and the ratio of the mean of the positional differences between all adjacent abnormal peaks to the total number of elements in the high-frequency detail component is used as the first proportion of the high-frequency detail component. If the number of abnormal peaks in the high-frequency detail component is less than or equal to 1, then the first proportion of the high-frequency detail component is equal to 1.

[0014] Preferably, the formula for obtaining the reactive power regulation of the photovoltaic inverter within each regulation cycle window is:

[0015]

[0016] In the formula, The reactive power regulation power of the photovoltaic inverter within the nth regulation cycle window. It is an exponential function with the natural constant as its base. The voltage burst anomaly degree for the (n-1)th control cycle window. The adjustable reactive power of the photovoltaic inverter. This represents the average effective voltage value during the (n-1)th control cycle window. This is the effective value of the rated voltage output by the photovoltaic inverter.

[0017] This application also provides a measurement and control device for a distributed photovoltaic power generation unit, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of the measurement and control method for a distributed photovoltaic power generation unit described above.

[0018] As can be seen from the above, the measurement and control device and method for a distributed photovoltaic power generation unit provided in this application have at least the following beneficial effects:

[0019] This application takes into account the high-frequency component characteristics of voltage waveform abnormalities at the photovoltaic grid connection point. Based on the Euclidean distance change between each element and its nearest neighbor in the high-frequency detail component, and combined with the difference in the Euclidean distance change between adjacent elements, it more accurately measures the abnormal characteristics of high-frequency voltage fluctuations reflected in the high-frequency detail component. This is conducive to timely and accurate adjustment of the reactive power output of the photovoltaic inverter, thereby achieving rapid suppression of voltage fluctuations at the photovoltaic grid connection point.

[0020] This application uses the high-frequency voltage fluctuation characteristics reflected in the high-frequency detail components and the abnormal peak characteristics presented in the high-frequency detail components to jointly measure the abnormality of sudden voltage fluctuations at the photovoltaic grid connection point, thereby more accurately adjusting the reactive power output of the photovoltaic inverter and ensuring the stability of the power grid operation in the power system.

[0021] Furthermore, this application, based on the deviation between the average effective voltage value at the photovoltaic grid connection point and the rated effective voltage value, and combined with the abnormality of sudden voltage fluctuations at the photovoltaic grid connection point, more accurately dynamically adjusts the reactive power of the photovoltaic inverter, thereby more effectively and quickly suppressing voltage fluctuations at the photovoltaic grid connection point and ensuring the stability of the power grid operation in the power system. Attached Figure Description

[0022] Figure 1 A flowchart illustrating the steps of a measurement and control method for a distributed photovoltaic power generation unit provided in this application. Detailed Implementation

[0023] The following description, in conjunction with the accompanying drawings, details the specific scheme of the measurement and control device and method for a distributed photovoltaic power generation unit provided in this application.

[0024] Please see Figure 1 The document illustrates a flowchart of a measurement and control method for a distributed photovoltaic power generation unit according to an embodiment of this application, including the following steps:

[0025] Step 1: Set up each control cycle window, and use the time series data of the grid connection point voltage of the photovoltaic grid connection point within the control cycle window to calculate the voltage change rate at each sampling time.

[0026] In this embodiment, the voltage data of the photovoltaic grid connection point is monitored. Specifically, a voltage transformer is used to collect the grid connection point voltage at the photovoltaic grid connection point. In this embodiment, the sampling rate of the grid connection point voltage is 1kHz.

[0027] In order to accurately and timely dynamically adjust the reactive power of the photovoltaic inverter, a sliding window method is used to set a control cycle window in the time series data of the grid connection point voltage. The time length of the control cycle window is 500ms, and the sliding step of the control cycle window is 50ms. The time series data of the grid connection point voltage within each control cycle window is obtained, which is used to achieve millisecond-level response for subsequent dynamic adjustment of reactive power.

[0028] Current technologies treat voltage deviation changes as a single factor for dynamic adjustment of the reactive power of photovoltaic (PV) inverters, neglecting sudden voltage fluctuations at the PV grid connection point. This makes it difficult to accurately and dynamically adjust the reactive power of PV inverters, thus failing to effectively and quickly smooth out voltage fluctuations at the PV grid connection point. Therefore, to more accurately and dynamically adjust the reactive power of PV inverters, it is necessary to effectively analyze sudden voltage fluctuations at the PV grid connection point.

[0029] To more clearly identify sudden voltage fluctuations at the photovoltaic grid connection point, for the time-series data of the grid connection point voltage within each control cycle window, the voltage change rate at each sampling moment within the control cycle window is calculated. The difference between the grid connection point voltage at each sampling moment and the previous sampling moment is calculated, and the ratio of this difference to the absolute value of the grid connection point voltage at the previous sampling moment is taken as the voltage change rate at each sampling moment. In the ratio calculation, to avoid the denominator being zero, a constant is added to the denominator to prevent it from being zero. The constant value ranges from 0.1 to 1, and in this embodiment, it is 0.5. Specifically, for sampling moment i, if... If the voltage change rate is not calculated directly using the formula for calculating the voltage change rate, then the voltage change rate at the first sampling moment cannot be calculated directly. Since the voltage change characteristics between adjacent sampling moments are similar, the voltage change rate at the first sampling moment is set to be the same as the voltage change rate at the second sampling moment.

[0030] The voltage change rate reflects the voltage change characteristics between adjacent sampling times at the photovoltaic grid connection point, and can more clearly reflect the sudden voltage fluctuations at the photovoltaic grid connection point. Therefore, the voltage change rate sequence of all sampling times in each control window is composed of time sequence and is recorded as the voltage change rate sequence of each control cycle window, which reflects the time change characteristics of the voltage change rate at the photovoltaic grid connection point.

[0031] Step 2: Analyze the anomalies of the high-frequency detail components of the voltage change rate at the photovoltaic grid connection point to obtain the high-frequency voltage fluctuations of the high-frequency detail components.

[0032] The intermittent and random nature of distributed photovoltaic (PV) power generation can cause sudden voltage fluctuations, making the voltage waveform at the PV grid connection point prone to anomalies. This results in complex high-frequency characteristics of the voltage rate of change over time. Therefore, to more accurately analyze the complex high-frequency characteristics of the voltage rate of change over time, high-frequency detail components of the voltage rate of change sequence are extracted for each control period window. Preferably, in this embodiment, the voltage rate of change sequence is used as a Discrete Wavelet Transform (DWT), where the wavelet basis function is the db4 function and the preset decomposition level is 4. The DWT is used to obtain the high-frequency detail components of the voltage rate of change sequence at each decomposition level, reflecting the high-frequency component characteristics of voltage waveform anomalies at the PV grid connection point.

[0033] In order to accurately extract the voltage waveform features of each element position in the high-frequency detail component, for each element in the high-frequency detail component of each decomposition layer, the K elements that are closest to each element in the high-frequency detail component are recorded as the nearest neighbors of each element in the high-frequency detail component. In this embodiment, Euclidean distance is used, but implementers may also use other distance measurement methods.

[0034] Furthermore, to analyze the Euclidean distance variation between each element and its nearest neighbors, this embodiment calculates the Euclidean distance between each element and its K nearest neighbors. The vector formed by these Euclidean distances according to the order of the nearest neighbors in the high-frequency detail components is denoted as the voltage characteristic distance vector of each element in the high-frequency detail components, reflecting the high-frequency characteristics of the voltage waveform at each element's position in the high-frequency detail components. The value of K ranges from 8% to 10% of the total number of elements in the high-frequency detail components, thus fully reflecting the Euclidean distance variation between each element and its nearest neighbors. In this embodiment, K is set to 10% of the total number of elements. If 10% of the total number of elements is not an integer, it is rounded up.

[0035] Generally, due to high-frequency abnormal fluctuations at the photovoltaic grid connection point, the voltage change rate sequence will exhibit complex fluctuations in the high-frequency detail components of each decomposition layer, resulting in significant differences in the voltage feature distance vectors between adjacent element positions in the high-frequency detail components.

[0036] Based on the above analysis, in this embodiment, the standard deviation of all elements within the voltage feature distance vector of each element in the high-frequency detail component is calculated, and the distance between each element in the high-frequency detail component and the voltage feature distance vector of its predecessor is calculated. The mean of the product of the standard deviation and the distance of all elements in the high-frequency detail component is taken as the voltage high-frequency fluctuation of the high-frequency detail component. In this embodiment, DTW distance (Dynamic Time Warping) is used to measure the distance between voltage feature distance vectors. Implementers may also use other existing distance measurement methods between vectors. This embodiment does not impose any special restrictions on this.

[0037] It should be noted that in the high-frequency detail component, the voltage feature distance vector of each element position is extracted using Euclidean distance. The standard deviation of the voltage feature distance vector can reflect the abnormal changes in the voltage waveform. Therefore, based on the standard deviation of the voltage feature distance vector and combined with the differences in the voltage feature distance vectors between adjacent elements, the high-frequency voltage fluctuations of the high-frequency detail component can be measured.

[0038] Among them, the high-frequency voltage fluctuation reflects the abnormal characteristics of high-frequency voltage fluctuation in the high-frequency detail components. If the voltage change rate sequence shows more significant abnormal fluctuations with high-frequency abrupt changes in the high-frequency detail components of the decomposition layer, the high-frequency voltage fluctuation is greater, and the reactive power output of the photovoltaic inverter needs to be adjusted in a timely and accurate manner to achieve rapid smoothing of voltage fluctuations at the photovoltaic grid connection point.

[0039] Step 3: Extract abnormal peaks by utilizing the fluctuation of the peak voltage change rate in the high-frequency detail components. By combining the proportion and density of the abnormal peaks with the high-frequency voltage fluctuation, the voltage sudden anomaly degree of each control cycle window can be obtained. Combined with the average distribution level of the effective voltage value of the grid connection point voltage within the control cycle window, the reactive power regulation power of the photovoltaic inverter within each control cycle window can be obtained.

[0040] Meanwhile, due to the complex high-frequency characteristics of the abnormal voltage waveform at the photovoltaic grid connection point, the voltage change rate sequence is prone to exhibiting abnormal peaks in the high-frequency detail components of each decomposition layer. The greater the density of abnormal peaks in the high-frequency detail components and the higher the complexity of the abnormal peaks, the more it reflects the sudden voltage fluctuations at the photovoltaic grid connection point.

[0041] Therefore, in order to more accurately analyze the abnormal peak features in the high-frequency detail components, the high-frequency detail components of the voltage change rate sequence in each decomposition layer are used as inputs to the AMPD (Automatic Multiscale Peak Detection) algorithm. The AMPD algorithm is used to obtain all peak points in the high-frequency detail components, and the voltage feature distance vector of each element in the high-frequency detail components is combined to obtain the voltage feature distance vector of each peak point in the high-frequency detail components. Since the voltage change rate at the abnormal peak position fluctuates drastically, the standard deviation of all elements in the voltage feature distance vector of each peak point is calculated. The mean of the standard deviations corresponding to the voltage feature distance vectors of all peak points is used as the screening threshold. Each peak point with a standard deviation greater than the screening threshold is recorded as an abnormal peak point in the high-frequency detail component, thereby accurately reflecting the drastic changes in the voltage change rate at the abnormal peak position.

[0042] Furthermore, the ratio between the number of all abnormal peaks in the high-frequency detail component and the total number of peaks in the high-frequency detail component is calculated and denoted as the peak proportion of the high-frequency detail component. The larger the peak proportion, the higher the complexity of the abnormal peaks in the high-frequency detail component, and the better it reflects the sudden voltage fluctuations at the photovoltaic grid connection point. At the same time, the positional difference between every two adjacent abnormal peaks in the high-frequency detail component is calculated, and the ratio between the mean of all positional differences between every two adjacent abnormal peaks and the total number of elements in the high-frequency detail component is denoted as the first proportion of the high-frequency detail component. The smaller the first proportion, the smaller the time interval between abnormal peaks in the high-frequency detail component, that is, the higher the density of the abnormal peak distribution, and the better it reflects the sudden voltage fluctuations at the photovoltaic grid connection point.

[0043] Based on the above analysis, using the aforementioned peak ratio and the first ratio, combined with the high-frequency voltage fluctuation, the voltage sudden anomaly degree for each control cycle window is calculated. In this embodiment, the specific calculation formula is as follows:

[0044] In the formula, For the voltage sudden anomaly degree of each control cycle window, The number of high-frequency detail components. The peak percentage of the s-th high-frequency detail component is denoted as . The first proportion of the s-th high-frequency detail component. Let be the voltage high-frequency fluctuation of the s-th high-frequency detail component. To avoid extremely small positive numbers with a denominator of zero, its purpose is to prevent the denominator from taking the value 0, and its range is 10. -6 -10 -5 In this embodiment, the value is 10. -6Specifically, if the number of anomalous spikes in the s-th high-frequency detail component is less than or equal to 1, then the first proportion of the s-th high-frequency detail component is set to 1, indicating that the anomalous spikes appearing in the high-frequency detail component do not have high-frequency characteristics.

[0045] In the formula for calculating the voltage burst anomaly degree, the peak ratio and the high-frequency voltage fluctuation are directly proportional to the voltage burst anomaly degree, while the first ratio is inversely proportional to the voltage burst anomaly degree. At the same time, the voltage burst anomaly characteristics of each control cycle window are measured by averaging.

[0046] Among them, the voltage burst anomaly degree reflects the degree of abnormality of sudden voltage fluctuations at the photovoltaic grid connection point. The more significant the sudden voltage fluctuation characteristics caused by the intermittency and randomness of distributed photovoltaic power generation, the worse the power quality at the photovoltaic grid connection point. Furthermore, the greater the degree of abnormality of sudden voltage fluctuations at the photovoltaic grid connection point, the greater the need to increase the adjustment of the reactive power output of the photovoltaic inverter, so as to achieve rapid suppression of voltage fluctuations at the photovoltaic grid connection point and ensure the stability of grid operation.

[0047] Furthermore, in order to dynamically adjust the reactive power of the photovoltaic inverter within each control cycle window, the effective voltage value of each control cycle window is first obtained. The process of obtaining the effective voltage value is existing technology. Preferably, in this embodiment, the AMPD peak detection algorithm is used to obtain all peak voltages of the grid connection point voltage within each control cycle window. Based on all peak voltages of the grid connection point voltage within each control cycle window, the average value of the effective voltage value of each control cycle window is calculated, which is used for subsequent dynamic adjustment of the reactive power of the photovoltaic inverter. It should be noted that the specific process of calculating the effective voltage value from the peak voltage is existing technology and will not be elaborated in this embodiment.

[0048] Based on the above analysis, the reactive power regulation of the photovoltaic inverter within each regulation cycle window is calculated:

[0049]

[0050] In the formula, The reactive power regulation power of the photovoltaic inverter within the nth regulation cycle window. It is an exponential function with the natural constant as its base. The voltage burst anomaly degree for the (n-1)th control cycle window. This refers to the adjustable reactive power of the photovoltaic inverter, which is 31% of the inverter's rated output capacity. The rated output capacity of the photovoltaic inverter is determined by its model. This represents the average effective voltage value during the (n-1)th control cycle window. The rated effective voltage output of the photovoltaic inverter is 220V. In this embodiment, the grid allowable deviation is +7% and -10% of the rated effective voltage, i.e., 198V to 235.4V. Specifically, the reactive power regulation power of the photovoltaic inverter is 0 during the first regulation cycle window.

[0051] Based on the deviation between the average effective voltage value at the photovoltaic grid connection point and the reference effective voltage value, and combined with the degree of abnormality of sudden voltage fluctuations at the photovoltaic grid connection point, the reactive power of the photovoltaic inverter is dynamically adjusted. Specifically, when the average effective voltage value is less than (1-10%) of the rated effective voltage value, the photovoltaic inverter automatically switches to capacitive reactive power output mode and adjusts the reactive power of the photovoltaic inverter to quickly raise the voltage, taking into account the sudden voltage fluctuations at the photovoltaic grid connection point. When the average effective voltage value is greater than (1+7%) of the rated effective voltage value, the photovoltaic inverter automatically switches to inductive reactive power absorption state to suppress excessive voltage rise, thereby more effectively and quickly smoothing out voltage fluctuations at the photovoltaic grid connection point.

[0052] Furthermore, by monitoring the voltage surge anomaly rate and the average effective voltage value in each control cycle window in real time, and updating the reactive power regulation of the photovoltaic inverter within the current control cycle window in real time, millisecond-level response for dynamic reactive power regulation is achieved. Subsequently, the reactive power regulation of the current control cycle window is transmitted to the photovoltaic inverter, which quickly smooths voltage fluctuations at the photovoltaic grid connection point, ensuring the stability of the power grid operation.

[0053] Based on the same inventive concept as the above method, this application embodiment also provides a measurement and control device for a distributed photovoltaic power generation unit, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any of the above-described measurement and control methods for a distributed photovoltaic power generation unit.

[0054] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Any equivalent structural or procedural transformations made based on the description and drawings of this application, or direct or indirect applications in other related technical fields, are similarly included within the protection scope of this application.

Claims

1. A measurement and control method for a distributed photovoltaic power generation unit, characterized in that, Includes the following steps: Each control cycle window is set up, and the voltage change rate at each sampling moment is calculated using the time-series data of the grid-connected point voltage within the control cycle window. The anomalies of the high-frequency detail components of the voltage change rate of the grid-connected point are analyzed to obtain the high-frequency voltage fluctuation of the high-frequency detail components. Abnormal peak points are extracted using the fluctuation of the peak voltage change rate in the high-frequency detail components. By combining the proportion and density of the abnormal peak points with the high-frequency voltage fluctuation, the voltage sudden anomaly degree of each control cycle window is obtained. Combined with the average distribution level of the effective voltage value of the grid-connected point voltage within the control cycle window, the reactive power regulation power of the photovoltaic inverter within each control cycle window is obtained. Voltage burst anomaly degree in each control cycle window The formula for obtaining the relation is: In the formula, The number of high-frequency detail components. The peak percentage of the s-th high-frequency detail component. The first proportion of the s-th high-frequency detail component. Let be the voltage high-frequency fluctuation of the s-th high-frequency detail component. To avoid extremely small positive numbers with a denominator of zero; The formula for obtaining the reactive power regulation of the photovoltaic inverter within each regulation cycle window is as follows: ； In the formula, The reactive power regulation power of the photovoltaic inverter within the nth regulation cycle window. It is an exponential function with the natural constant as its base. The voltage burst anomaly degree for the (n-1)th control cycle window. For the adjustable reactive power of photovoltaic inverters, This represents the average effective voltage value during the (n-1)th control cycle window. This is the effective value of the rated voltage output by the photovoltaic inverter.

2. The measurement and control method for a distributed photovoltaic power generation unit as described in claim 1, characterized in that, Calculate the difference between the grid connection point voltage at each sampling time and the voltage at the previous sampling time. Use the ratio of this difference to the absolute value of the grid connection point voltage at the previous sampling time as the voltage change rate at each sampling time.

3. The measurement and control method for a distributed photovoltaic power generation unit as described in claim 1, characterized in that, The voltage change rate at all sampling times within the control window is arranged in an inter-order sequence to form a voltage change rate sequence. The high-frequency detail components of each decomposition layer of the voltage change rate sequence are extracted using discrete wavelet transform. The elements closest to each element in the high-frequency detail component are recorded as the nearest neighbors of each element in the high-frequency detail component. The vector formed by the distance between each element and its nearest neighbors according to the sorting of the nearest neighbors in the high-frequency detail component is used as the voltage feature distance vector of each element.

4. The measurement and control method for a distributed photovoltaic power generation unit as described in claim 3, characterized in that, Calculate the standard deviation of all elements within the voltage characteristic distance vector of each element in the high-frequency detail component, calculate the distance between each element in the high-frequency detail component and the voltage characteristic distance vector of its predecessor, and take the mean of the product of the standard deviation and the distance of all elements in the high-frequency detail component as the high-frequency voltage fluctuation of the high-frequency detail component.

5. The measurement and control method for a distributed photovoltaic power generation unit as described in claim 3, characterized in that, Extract all peak points from the high-frequency detail components, calculate the average standard deviation of the voltage characteristic distance vector of each peak point as the screening threshold, and identify peak points with standard deviations greater than the screening threshold as abnormal spikes.

6. The measurement and control method for a distributed photovoltaic power generation unit as described in claim 1, characterized in that, The ratio of all abnormal peaks in the high-frequency detail component to the total number of peaks in the high-frequency detail component is taken as the peak percentage of the high-frequency detail component.

7. The measurement and control method for a distributed photovoltaic power generation unit as described in claim 1, characterized in that, Calculate the positional difference between two adjacent anomalous peaks in the high-frequency detail component. The ratio of the mean of the positional differences between all adjacent anomalous peaks to the total number of elements in the high-frequency detail component is used as the first proportion of the high-frequency detail component. If the number of anomalous peaks in the high-frequency detail component is less than or equal to 1, then the first proportion of the high-frequency detail component is equal to 1.

8. A measurement and control device for a distributed photovoltaic power generation unit, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the measurement and control method for a distributed photovoltaic power generation unit as described in any one of claims 1-7.

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