Real-time monitoring method and system for new energy power

Abstract

The invention discloses a real-time monitoring method and system for new energy electric power, relates to the technical field of new energy electric power system monitoring and control, and aims to construct an early warning model so as to accurately capture a sudden change point of power change, improve the accuracy of prediction switching time, provide early warning for normal operation of electric power equipment and solve the problems that new energy electric power is greatly influenced by the environment and the operation is not convenient. In the prior art, the output power has intermittence, the state switching time is difficult to predict accurately, the previous intermittent duration in a plurality of previous monitoring periods is obtained based on the predicted switching time, the stability of the intermittent duration is quantized, the predicted switching duration is obtained, and the new energy electric power is supplied to the subsequent new energy electric power according to the intermittent rule and duration of the new energy electric power. And data support is provided for the duration of switching and using the standby power supply.

Description

Technical Field

[0001] The present invention relates to the technical field of monitoring and controlling new energy power systems, and in particular to a real-time monitoring method and system for new energy power. Background Art

[0002] As the proportion of renewable energy (such as solar and wind power) in the power system gradually increases, the real-time monitoring and management of renewable energy power has become increasingly important. However, since the power generation principle of renewable energy power is significantly affected by environmental factors (such as light intensity and wind speed changes), its output power is significantly intermittent. This intermittency not only increases the difficulty of power system scheduling, but also poses a threat to the normal operation of power equipment.

[0003] In existing technologies, renewable energy power is significantly affected by the environment, and the intermittent nature of its output power makes it difficult to accurately predict its state switching time. This not only affects the dispatch efficiency of the power system, but can also lead to damage to power equipment or power supply interruptions due to inaccurate predictions. Due to the volatility of renewable energy intermittent power, existing technologies often struggle to provide reliable basis for predicting switching times. This can lead to problems such as unstable power supply and equipment overload during actual switching processes due to inaccurate switching time predictions. Summary of the Invention

[0004] The object of the present invention is to provide a real-time monitoring method and system for renewable energy power to solve at least one of the above-mentioned problems in the prior art.

[0005] In a first aspect, a real-time monitoring method for renewable energy power comprises:

[0006] During the previous monitoring period, the output power of renewable energy power was analyzed to identify previous intermittent phenomena and obtain a reference intermittent change curve;

[0007] During the real-time monitoring period, the output power of renewable energy power is analyzed and compared with the reference intermittent change curve of previous intermittent phenomena to assess the current risk level of renewable energy power intermittency;

[0008] If the power outage risk is high, the real-time monitored power output is analyzed in real time to obtain the early warning reference slope, and an early warning model is constructed to obtain the predicted switching time;

[0009] Based on the predicted switching time, the previous intermittent durations in multiple previous monitoring cycles are obtained and analyzed to obtain the predicted switching duration and complete the switching of new energy power.

[0010] In a second aspect, a real-time monitoring system for renewable energy power is provided, comprising:

[0011] Previous monitoring and analysis module: Analyze the output power of renewable energy power in previous monitoring cycles, identify previous intermittent phenomena, and obtain a reference intermittent change curve;

[0012] Comparison risk assessment module: During the real-time monitoring period, the output power of renewable energy power is analyzed and compared with the reference intermittent change curve of previous intermittent phenomena to assess the current degree of intermittent risk of renewable energy power;

[0013] Switching time prediction module: If the power interruption risk is high, the real-time monitored power output is analyzed in real time to obtain the early warning reference slope, and an early warning model is constructed to obtain the predicted switching time;

[0014] Switching duration prediction module: Based on the predicted switching time, the module obtains the previous intermittent durations in multiple previous monitoring cycles and analyzes them to obtain the predicted switching duration and complete the switching of new energy power.

[0015] Beneficial effects of the present invention:

[0016] 1. The present invention analyzes the output power of renewable energy power during previous monitoring cycles, identifies past intermittent phenomena, and obtains a reference intermittent change curve. The real-time power change curve during the real-time monitoring cycle is then compared with the reference intermittent change curve. The overall matching degree between the real-time power characteristics and the historical intermittent pattern is quantified through the two dimensions of change trend similarity and change amplitude similarity. This improves the monitoring accuracy of renewable energy power output power and provides data support for subsequent power warnings.

[0017] 2. If the risk of power intermittency is high, the present invention conducts real-time analysis on the real-time monitored power output and constructs an early warning model, so as to accurately capture the mutation point of power change, improve the accuracy of predicted switching time, and provide early warning for the normal operation of power equipment. It solves the problem that new energy power is greatly affected by the environment, the output power is intermittent, and it is difficult to accurately predict its state switching time. Based on the predicted switching time, the previous intermittent duration in multiple previous monitoring cycles is obtained, and the stability of the intermittent duration is quantified to obtain the predicted switching duration, which provides data support for the subsequent switching time based on the law and duration of the intermittent power of new energy power. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0019] Figure 1 This is a flowchart of the steps of a real-time monitoring method for renewable energy power according to the present invention;

[0020] Figure 2 It is a schematic diagram of a real-time monitoring system for new energy power according to the present invention. DETAILED DESCRIPTION

[0021] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described 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 making creative efforts should fall within the scope of protection of the present invention.

[0022] Example 1

[0023] like Figure 1 As shown, an embodiment of the present invention provides a real-time monitoring method for new energy power, which specifically includes the following steps:

[0024] Step 1: Analyze the output power of renewable energy power during previous monitoring cycles, identify previous intermittent phenomena, and obtain a reference intermittent change curve;

[0025] In some embodiments, the previous monitoring period is evenly divided into a number of previous monitoring time points;

[0026] Among them, the intervals between adjacent previous monitoring time points after division are equal in length;

[0027] Obtain the previous output power corresponding to each previous monitoring time point, perform difference processing on it with the rated output power of the new energy source, and obtain the previous power difference value;

[0028] Compare the previous power difference value with the previous power difference threshold value. The process is as follows:

[0029] If the previous power difference value is greater than the previous power difference threshold, it means that the previous output power at the analyzed previous monitoring time point is significantly different from the rated output power of the new energy source, and it is suspected to be a previous intermittent time point;

[0030] If the previous power difference is less than or equal to the previous power difference threshold, it means that the difference between the previous output power at the analyzed previous monitoring time point and the rated output power of the new energy source is small, and it is a normal power time point;

[0031] Count the suspected past intermittent time points, and sort them according to the time series corresponding to the suspected past intermittent time points to construct the suspected past intermittent sorting;

[0032] Extract the first suspected past intermission time point and the last suspected past intermission time point in the suspected past intermission sequence respectively, and obtain the period between the first suspected past intermission time point and the last suspected past intermission time point as the suspected past intermission period;

[0033] Among them, the suspected previous intermittent period includes all suspected previous intermittent points in the suspected previous intermittent sequence;

[0034] Calculate the standard deviation of the previous power difference value corresponding to each suspected previous intermittent time point in the suspected previous intermittent period, and output the previous difference standard deviation value;

[0035] If the standard deviation of the previous difference is less than or equal to the standard deviation threshold of the previous difference, it means that the previous output power differed greatly from the rated output power of the new energy source during the suspected previous intermittent period and was relatively stable, and it is determined that a previous intermittent phenomenon occurred during the suspected previous intermittent period;

[0036] If the previous difference standard deviation value is greater than the previous difference standard deviation threshold, it means that the previous output power differed greatly from the rated output power of the new energy during the suspected previous intermittent period and was relatively unstable, and it was determined that no previous intermittent phenomenon occurred during the suspected previous intermittent period;

[0037] With the X-axis representing time and the Y-axis representing power, the previous output power corresponding to each previous monitoring time point in the previous monitoring period is input into the two-dimensional coordinate system to construct a previous power change curve;

[0038] Intercept the coordinates of the starting point of the previous power change curve and the local previous power change curve between the suspected previous intermittent time point ranked first in the suspected previous intermittent sequence as a reference intermittent change curve;

[0039] Step 2: During the real-time monitoring period, analyze the output power of renewable energy power and compare it with a reference intermittent change curve that has repeatedly experienced intermittent phenomena in the past to assess whether there is an intermittent risk in the current renewable energy power;

[0040] In some embodiments, the real-time monitoring period is evenly divided into a number of real-time monitoring time points;

[0041] The intervals between adjacent real-time monitoring time points are equal in length, and the method of dividing the real-time monitoring period is consistent with the method of dividing the previous monitoring period;

[0042] During the real-time monitoring period, the real-time output power corresponding to each real-time monitoring point is obtained, and a real-time power change curve is constructed with the X-axis as time and the Y-axis as power;

[0043] The real-time power change curve is divided according to the local real-time power change curves between adjacent real-time monitoring time points to obtain multiple real-time change sub-curves;

[0044] The slope of each real-time changing sub-curve is obtained through the slope calculation formula, and the sum and average calculation are performed to obtain the real-time changing slope;

[0045] Similarly, the reference intermittent change curve is divided according to the local reference intermittent change curves between adjacent previous monitoring time points to obtain multiple reference change sub-curves;

[0046] Obtain the slope of each reference change sub-curve using the slope calculation formula, and perform summation and mean calculation to obtain the reference change slope;

[0047] The real-time change slope and the reference change slope are used as a set of change trend comparison groups;

[0048] Extract all the peak point coordinates and trough point coordinates on the real-time power change curve, and use the coordinate point distance formula to obtain the distance between adjacent peak point coordinates and trough point coordinates (or the distance between adjacent trough point coordinates and peak point coordinates) as the unit real-time change amplitude;

[0049] The real-time change amplitudes of all units are averaged and the real-time change amplitude mean is output;

[0050] Similarly, extract all the peak and trough coordinates on the reference intermittent change curve, and use the coordinate point distance formula to obtain the distance between adjacent peak and trough coordinates (or the distance between adjacent trough coordinates and peak coordinates) as the unit reference change amplitude;

[0051] All unit reference change amplitudes are averaged and the average reference change amplitude is output;

[0052] The real-time change amplitude mean and the reference change amplitude mean are used as a set of change amplitude comparison groups;

[0053] Input the change trend comparison group and the change amplitude comparison group into the Euclidean distance calculation formula respectively, and output the comparison similarity value ;

[0054] Specifically, the Euclidean distance calculation formula is: ,in, and They are respectively expressed as the real-time change slope and reference change slope within the change trend comparison group. and They are respectively expressed as the mean of the real-time change amplitude and the mean of the reference change amplitude within the change amplitude comparison group;

[0055] It is understandable that the meaning of the comparison similarity value is:

[0056] Meaning 1: In terms of comparison, the trend and amplitude of the curve are compared. The similarity between the overall trend of the real-time power change curve and the overall trend of the reference intermittent change curve is compared. The similarity between the overall amplitude of the real-time change curve and the overall amplitude of the reference intermittent change curve is compared. This numerical quantification of similarity provides an objective judgment basis for real-time monitoring of new energy power systems and assists operation and maintenance personnel in responding to anomalies in a timely manner.

[0057] Meaning 2: From a mathematical perspective, the change curve and change amplitude are considered as coordinate points in a two-dimensional space, and the Euclidean distance is used to calculate the "spatial distance" between real-time data and historical reference data. A closer distance indicates a higher similarity between the real-time power change characteristics and the historical intermittent phenomena, and a higher intermittent risk. A farther distance indicates a lower similarity between the real-time power change characteristics and the historical intermittent phenomena, and a lower intermittent risk.

[0058] Compare the similarity values ​​of multiple comparisons and extract the reference intermittent change curve corresponding to the minimum similarity value as the target reference curve;

[0059] Extract the previous intermittent period on the target reference curve, obtain the duration corresponding to the previous intermittent period, calculate the ratio with the duration of the previous monitoring cycle, and output the previous intermittent duration ratio;

[0060] During the previous intermittent period, the previous power difference value corresponding to each previous intermittent time point is obtained and averaged, and the ratio is calculated with the rated output power of the new energy source to obtain the previous difference ratio;

[0061] The product of the previous interval duration ratio and the previous difference ratio is calculated and the output is the interval risk value;

[0062] The intermittent risk value is compared with the intermittent risk threshold as follows:

[0063] If the intermittent risk value is greater than the intermittent risk threshold, it indicates that the intermittent risk is high, and a high intermittent probability signal is generated;

[0064] If the intermittent risk value is less than or equal to the intermittent risk threshold, the intermittent risk is low and a small intermittent probability signal is generated;

[0065] The specific implementation plan of this embodiment is: in the previous monitoring period, the output power of the new energy power is analyzed, the previous intermittent phenomenon is identified, and a reference intermittent change curve is obtained. The real-time power change curve in the real-time monitoring period is combined and compared with the reference intermittent change curve. Through the two dimensions of change trend similarity and change amplitude similarity, the overall matching degree between the real-time power characteristics and the historical intermittent pattern is quantified, thereby improving the monitoring accuracy of the output power of the new energy power and providing data support for subsequent power warnings.

[0066] Example 2

[0067] Step 3: If the power outage risk is high, analyze the real-time monitored power output power, build an early warning model, and obtain a predicted switching time;

[0068] In some embodiments, on the real-time power change curve, the slopes of adjacent real-time change sub-curves are respectively input into the Euclidean distance formula, and the real-time sub-slope difference value is output. ;

[0069] Specifically, the Euclidean distance formula is: ,in, Expressed as the first The slope of the sub-curve changes in real time, Expressed as the first The slope of the real-time change sub-curve, n represents the total number of real-time change sub-curves on the real-time power change curve;

[0070] It should be noted that the purpose of using the Euclidean distance formula is:

[0071] Euclidean distance is essentially the straight-line distance between two points in multidimensional space. Using mathematical formulas, it converts the abstract "slope difference" into a concrete, measurable value. This not only captures sudden changes in local adjacent slopes (such as a sharp turn between two sub-curves), but also comprehensively assesses the fluctuation of the entire curve by summarizing the distance values ​​of all adjacent slopes. This provides key characteristic parameters (such as the location of the turning point and the magnitude of the slope change) for subsequent real-time output power warnings, improving the accuracy of switching time predictions.

[0072] If the real-time sub-slope difference value is greater than the real-time sub-slope threshold, it means that on the real-time power change curve, the slopes of all adjacent real-time change sub-curves are greatly different, and a large sub-slope difference signal is generated;

[0073] If the real-time sub-slope difference value is less than or equal to the real-time sub-slope threshold, it means that on the real-time power change curve, the slope differences of all adjacent real-time change sub-curves are small, and a small sub-slope difference signal is generated;

[0074] If a large sub-slope difference signal is generated, the slopes of all real-time change sub-curves on the real-time power change curve are compared, and the maximum slope of the real-time change sub-curve is extracted as the warning reference slope;

[0075] If a small sub-slope difference signal is generated, the slopes of all real-time change sub-curves on the real-time power change curve are averaged and output as a warning reference slope;

[0076] Obtain the end point coordinates on the real-time power change curve, and combine it with the warning reference slope to build a warning model, and obtain the warning model equation: ,in, It is expressed as the early warning benchmark slope, and b is expressed as a constant;

[0077] The intermittent output power value is input into the early warning model equation, and the output is the predicted switching time;

[0078] It should be noted that the meaning of predicted switching time is: based on the real-time power change curve and early warning model, the time point when the renewable energy power system switches from the current state to another state (such as from normal power supply to backup power supply, from full load operation to power rationing mode, etc.) is predicted. Since renewable energy power will have intermittent periods due to environmental influences, it is necessary to switch the renewable energy power output to ensure the normal operation of power equipment;

[0079] Step 4: Based on the predicted switching time, obtain the previous intermittent durations in multiple previous monitoring cycles and analyze them to obtain the predicted switching duration and complete the new energy power switching;

[0080] In some embodiments, a previous intermittent period in a previous monitoring cycle is arbitrarily selected, and the duration corresponding to the previous intermittent period is obtained as the previous intermittent duration;

[0081] It should be noted that the previous intermittent period is the duration of the period corresponding to the previous intermittent phenomenon judged to have occurred within the suspected previous intermittent period of the previous monitoring period;

[0082] Count all the previous intermittent durations in the previous monitoring period and input them into the coefficient of variation formula respectively, and output the previous intermittent stability value ;

[0083] Specifically, the coefficient of variation formula is: ,in, It is obtained by calculating the standard deviation of all previous interval durations in the previous monitoring period. It is obtained by calculating the average of all previous interval durations in the previous monitoring period;

[0084] Calculate the variance of all previous intermittent stability values ​​corresponding to previous monitoring periods and output the intermittent duration stability value;

[0085] It can be explained that the intermittent duration stability value means that, in the time dimension, it reflects the fluctuation of the intermittent duration of the renewable energy power system over multiple previous monitoring cycles. From a data perspective, it can quantify the stability of the intermittent duration, providing data support for the subsequent switching to the backup power supply based on the pattern and duration of the intermittent power of renewable energy power.

[0086] If the intermittent duration stability value is less than or equal to the intermittent duration stability threshold, it means that the intermittent durations that occurred in multiple previous cycles are relatively stable, and an intermittent duration stability signal is generated;

[0087] If the intermittent duration stability value is greater than the intermittent duration stability threshold, it means that the intermittent durations that occurred in multiple previous cycles were relatively fluctuating, and an intermittent duration fluctuation signal is generated;

[0088] If an intermittent duration stability signal is generated, the previous intermittent stability values ​​corresponding to all previous monitoring periods are averaged and output to obtain the predicted switching duration;

[0089] If an intermittent duration fluctuation signal is generated, the maximum intermittent duration corresponding to each previous monitoring period is extracted and averaged, and the predicted switching duration is output;

[0090] The specific implementation plan of this embodiment is: if the risk of power intermittency is large, the real-time monitored power output power is analyzed in real time, and an early warning model is constructed, so as to accurately capture the mutation points of power changes, improve the accuracy of predicted switching time, and provide early warning for the normal operation of power equipment. It solves the problem that new energy power is greatly affected by the environment, the output power is intermittent, and it is difficult to accurately predict its state switching time. Based on the predicted switching time, the previous intermittent duration in multiple previous monitoring cycles is obtained, and the stability of the intermittent duration is quantified to obtain the predicted switching duration, which provides data support for the subsequent switching time based on the law and duration of intermittent power of new energy power.

[0091] Example 3

[0092] like Figure 2 As shown, an embodiment of the present invention provides a real-time monitoring system for new energy power, including the following modules:

[0093] Previous monitoring and analysis module: Analyze the output power of renewable energy power in previous monitoring cycles, identify previous intermittent phenomena, and obtain a reference intermittent change curve;

[0094] Comparison risk assessment module: During the real-time monitoring period, the output power of renewable energy power is analyzed and compared with the reference intermittent change curve of previous intermittent phenomena to assess the current degree of intermittent risk of renewable energy power;

[0095] Switching time prediction module: If the power interruption risk is high, the real-time monitored power output is analyzed in real time to obtain the early warning reference slope, and an early warning model is constructed to obtain the predicted switching time;

[0096] Switching duration prediction module: Based on the predicted switching time, the module obtains the previous intermittent durations in multiple previous monitoring cycles and analyzes them to obtain the predicted switching duration and complete the switching of new energy power.

[0097] The above formulas are all dimensionless and numerical calculations. The formulas are obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formulas are set by technicians in this field according to actual conditions.

[0098] The above is a detailed description of an embodiment of the present invention. However, the content described is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A real-time monitoring method for renewable energy power, characterized in that: The following steps are involved: During the previous monitoring period, the output power of renewable energy power was analyzed to identify previous intermittent phenomena and obtain a reference intermittent change curve; During the real-time monitoring period, the output power of renewable energy power is analyzed and compared with the reference intermittent change curve of previous intermittent phenomena to assess the current risk level of renewable energy power intermittency; If the power outage risk is high, the real-time monitored power output is analyzed in real time to obtain the early warning reference slope, and an early warning model is constructed to obtain the predicted switching time; Based on the predicted switching time, the previous intermittent durations in multiple previous monitoring cycles are obtained and analyzed to obtain the predicted switching duration and complete the switching of new energy power.

2. A real-time monitoring method for new energy power according to claim 1, characterized in that: The previous process for identifying intermittent phenomena is as follows: Divide the previous monitoring period into several previous monitoring time points; Obtain the previous output power corresponding to each previous monitoring time point, perform subtraction processing on it with the rated output power of the new energy source, and obtain the previous power difference value. If it is greater than the previous power difference threshold, it is a suspected previous intermittent time point; Sort multiple suspected past intermittent time points according to time series, construct a suspected past intermittent sorting, and take the period between the first suspected past intermittent time point and the last suspected past intermittent time point in the sorting as the suspected past intermittent period; The standard deviation of the previous power difference value corresponding to each suspected previous intermittent time point in the suspected previous intermittent period is calculated, and the previous difference standard deviation value is output. If the previous difference standard deviation value is less than or equal to the previous difference standard deviation threshold, a previous intermittent phenomenon occurs.

3. A real-time monitoring method for new energy power according to claim 1, characterized in that: The output power of renewable energy power is analyzed and compared with the reference intermittent change curve that has repeatedly appeared in the past intermittent phenomena. The process is as follows: The real-time monitoring period is evenly divided into several real-time monitoring time points, and the real-time output power corresponding to each real-time monitoring time point is obtained. A real-time power change curve is constructed and divided to obtain multiple real-time change sub-curves. The slopes of the real-time change sub-curves are obtained and averaged to obtain the real-time change slopes. The reference intermittent change curve is divided into multiple reference change sub-curves, and the slopes of the reference change sub-curves are obtained, and the reference change slopes are obtained by averaging the slopes. Combining the real-time change slope and the reference change slope into a set of change trend comparison groups; Extract all the peak and trough coordinates on the real-time power change curve and all the peak and trough coordinates on the reference intermittent change curve respectively, and obtain the unit real-time change amplitude and unit reference change amplitude through the coordinate point distance formula. Then perform averaging processing on them respectively to obtain the mean of the real-time change amplitude and the mean of the reference change amplitude; Combining the real-time change amplitude mean and the reference change amplitude mean into a change amplitude comparison group; The change trend comparison group and the change amplitude comparison group are respectively input into the Euclidean distance calculation formula, and the comparison similarity value is output.

4. A real-time monitoring method for new energy power according to claim 1, characterized in that: The process of assessing the current risk level of renewable energy power intermittency is as follows: Extract the reference intermittent change curve corresponding to the minimum comparison similarity value as the target reference curve; Extract the previous intermittent period on the target reference curve, obtain the duration corresponding to the previous intermittent period, calculate the ratio with the duration of the previous monitoring cycle, and output the previous intermittent duration ratio; During the previous intermittent period, the previous power difference value corresponding to each previous intermittent time point is obtained and averaged, and the ratio is calculated with the rated output power of the new energy source to obtain the previous difference ratio; The product of the previous intermittent duration ratio and the previous difference ratio is calculated and the output is the intermittent risk value. If the intermittent risk value is greater than the intermittent risk threshold, a large intermittent probability signal is generated.

5. A real-time monitoring method for renewable energy power according to claim 1, characterized in that: The method for obtaining the early warning benchmark slope is: On the real-time power change curve, the slopes of adjacent real-time change sub-curves are respectively input into the Euclidean distance formula, and the real-time sub-slope difference value is output; If the real-time sub-slope difference value is greater than the real-time sub-slope threshold, a sub-slope difference large signal is generated. The slopes of all real-time change sub-curves on the real-time power change curve are compared, and the maximum slope of the real-time change sub-curve is extracted as the warning reference slope. If the real-time sub-slope difference value is less than or equal to the real-time sub-slope threshold, a sub-slope difference small signal is generated, and the slopes of all real-time change sub-curves on the real-time power change curve are averaged to obtain the warning reference slope.

6. A real-time monitoring method for renewable energy power according to claim 1, characterized in that: The process of building the early warning model is as follows: Obtain the end point coordinates on the real-time power change curve, and combine it with the warning reference slope to build a warning model, and obtain the warning model equation: ,in, It is expressed as the early warning benchmark slope, and b is expressed as a constant.

7. A real-time monitoring method for renewable energy power according to claim 1, characterized in that: The predicted switching time is obtained as follows: The intermittent output power value is input into the early warning model equation, and the output is the predicted switching time.

8. A real-time monitoring method for renewable energy power according to claim 1, characterized in that: Obtain the previous pause durations in multiple previous monitoring cycles and analyze them. The process is as follows: Randomly select a previous intermittent period in the previous monitoring cycle, obtain the duration corresponding to the previous intermittent period, and use it as the previous intermittent duration. Count all previous intermittent durations in the previous monitoring cycle and input them into the coefficient of variation formula respectively. Output the previous intermittent stable value, perform averaging processing, and output the intermittent duration stable value.

9. A real-time monitoring method for renewable energy power according to claim 1, characterized in that: The process of obtaining the predicted switching duration is as follows: If the intermittent duration stability value is less than or equal to the intermittent duration stability threshold, an intermittent duration stability signal is generated, and the previous intermittent stability values ​​corresponding to all previous monitoring periods are averaged to output the predicted switching duration; If the intermittent duration stability value is greater than the intermittent duration stability threshold, an intermittent duration fluctuation signal is generated, the maximum previous intermittent duration corresponding to each previous monitoring period is extracted, and the signal is averaged to obtain the predicted switching duration.

10. A real-time monitoring system for new energy power, characterized in that: include: Previous monitoring and analysis module: Analyze the output power of renewable energy power in previous monitoring cycles, identify previous intermittent phenomena, and obtain a reference intermittent change curve; Comparison risk assessment module: During the real-time monitoring period, the output power of renewable energy power is analyzed and compared with the reference intermittent change curve of previous intermittent phenomena to assess the current degree of intermittent risk of renewable energy power; Switching time prediction module: If the power interruption risk is high, the real-time monitored power output is analyzed in real time to obtain the early warning reference slope, and an early warning model is constructed to obtain the predicted switching time; Switching duration prediction module: Based on the predicted switching time, the module obtains the previous intermittent durations in multiple previous monitoring cycles and analyzes them to obtain the predicted switching duration and complete the switching of new energy power.

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