A new energy equipment dynamic monitoring method, system, medium and product

Abstract

This invention relates to a method, system, medium, and product for dynamic monitoring of new energy equipment, specifically in the field of new energy equipment monitoring. By employing the aforementioned technical solution, the monitoring system comprehensively analyzes current fluctuation characteristics, load change characteristics, and environmental impact characteristics, constructing a dual-trajectory monitoring model consisting of current characteristic trajectories and load characteristic trajectories. This method not only considers the dynamic changes in current and load but also calculates the degree of matching between current and load changes. Furthermore, it incorporates the influence of environmental factors to correct the correlation between the current and load characteristic trajectories, thereby enabling timely detection of operational anomalies in new energy equipment and making the monitoring results more accurate and reliable. When a dangerous operating state occurs, the monitoring system automatically controls the new energy equipment to stop operating, effectively preventing equipment damage and safety accidents. Compared to traditional single-parameter monitoring methods, this multi-dimensional, dynamic monitoring method has stronger early warning capabilities and higher reliability.

Description

Technical Field

[0001] This application relates to the field of new energy equipment monitoring, and in particular to a method, system, medium, and product for dynamic monitoring of new energy equipment. Background Technology

[0002] With the rapid development of new energy technologies, new energy equipment is being used more and more widely in industrial production and daily life. The safe and stable operation of new energy equipment is directly related to electricity safety and production efficiency; therefore, real-time monitoring and effective management of new energy equipment are of great significance.

[0003] Currently, the monitoring of new energy equipment mainly adopts a periodic inspection method. This involves checking the equipment at preset time intervals and recording basic parameters such as current and voltage. Monitoring personnel then compare these basic parameters with preset threshold values. When a parameter exceeds the preset threshold, an alarm signal is issued to indicate a potential abnormality in the new energy equipment.

[0004] However, due to the complex and variable operating environment of new energy equipment, the equipment load also frequently changes dynamically. Especially in severe weather or when the power grid fluctuates greatly, environmental and load factors can significantly affect the operating parameters of new energy equipment, causing the monitoring results to deviate from the actual operating status, making it impossible to detect potential equipment failures in time and affecting the safe operation of the equipment. Summary of the Invention

[0005] This application provides a method, system, medium, and product for dynamic monitoring of new energy equipment, which can improve the accuracy of monitoring the operating status of new energy equipment.

[0006] Firstly, this application provides a dynamic monitoring method for new energy equipment, applied to a monitoring system. The method includes: collecting current fluctuation characteristics, load change characteristics, and environmental impact characteristics of the new energy equipment; the current fluctuation characteristics include amplitude, frequency, and phase, where amplitude refers to the peak value of the current, frequency refers to the periodicity of the current change, and phase refers to the time lead or lag of the current waveform; the load change characteristics include power curves and power consumption patterns; and the environmental impact characteristics include ambient temperature and electromagnetic interference. Based on the amplitude, frequency, and phase, a current characteristic trajectory is constructed, which represents the dynamic current change process during the operation of the new energy equipment. The slope of the power curve and the periodicity of the power consumption pattern are extracted from the load change characteristics. The system employs several methods: First, it constructs a load characteristic trajectory to represent the dynamic load changes during the operation of the new energy equipment. Second, it determines an environmental influence coefficient based on ambient temperature and electromagnetic interference to represent the intensity of their impact on the operation of the new energy equipment. Third, it compares the current characteristic trajectory and the load characteristic trajectory over time to calculate the correlation, which represents the degree of matching between current changes and load changes. Fourth, it applies the environmental influence coefficient to the correlation to obtain a modified coupling characteristic. Fifth, it determines the equipment's operating status based on the modified coupling characteristic, including safe operation, early warning operation, and dangerous operation. Sixth, it controls the new energy equipment to stop operating when the equipment is in a dangerous operating state.

[0007] By adopting the above technical solution, the monitoring system comprehensively analyzes current fluctuation characteristics, load change characteristics, and environmental impact characteristics, constructing a dual-trajectory monitoring model of current characteristic trajectory and load characteristic trajectory. This method not only considers the dynamic changes in current and load but also calculates the matching degree between current and load changes. Furthermore, it incorporates the influence of environmental factors to correct the correlation between the current and load characteristic trajectories, thereby promptly detecting operational anomalies in new energy equipment and making the monitoring results more accurate and reliable. When a dangerous operating state occurs, the monitoring system automatically controls the new energy equipment to stop operating, effectively preventing equipment damage and safety accidents. Compared to traditional single-parameter monitoring methods, this multi-dimensional, dynamic monitoring method has stronger early warning capabilities and higher reliability.

[0008] In conjunction with some embodiments of the first aspect, in some embodiments, a current feature trajectory is constructed based on amplitude, frequency, and phase, specifically including: mapping amplitude, frequency, and phase in a three-dimensional coordinate system to obtain current feature points; performing time-series connection on the current feature points to obtain the original current trajectory; calculating a current feature vector based on the original current trajectory, the current feature vector including trajectory curvature, trajectory length, and trajectory direction; establishing a feature space model based on the current feature vector, and using the feature space model as the current feature trajectory.

[0009] By employing the above technical solution, the monitoring system maps amplitude, frequency, and phase in a three-dimensional coordinate system to obtain current feature points, and then connects these current feature points in a time sequence to innovatively construct a current feature trajectory. This method not only intuitively reflects the dynamic process of current change, but also quantitatively describes the characteristics of current change in various dimensions through current feature vectors. Compared with traditional waveform analysis methods, it can monitor current changes more comprehensively.

[0010] In conjunction with some embodiments of the first aspect, in some embodiments, the slope of the power curve and the periodicity of the electricity consumption pattern are extracted from the load change characteristics to construct a load feature trajectory. Specifically, this includes: determining a periodic load pattern based on the periodicity of the electricity consumption pattern; mapping the slope of the power curve and the periodic load pattern on a two-dimensional plane to generate load change feature points; and connecting the load change feature points in chronological order to obtain the load feature trajectory.

[0011] By adopting the above technical solution, the monitoring system analyzes the periodic characteristics of electricity consumption patterns to determine periodic load patterns, and constructs a load characteristic trajectory on a two-dimensional plane by combining the slope of the power curve. This considers both the instantaneous characteristics of load changes (power curve slope) and long-term operating characteristics (periodic load patterns). The monitoring system connects load change characteristic points in chronological order to form a load characteristic trajectory, which can completely record the load change process. This dual-feature analysis method is more advantageous than simply monitoring power changes, and can more accurately reflect the actual operating status of new energy equipment, providing a more reliable basis for equipment anomaly detection.

[0012] In conjunction with some embodiments of the first aspect, in some embodiments, the current characteristic trajectory and the load characteristic trajectory are compared in time series to calculate the correlation. The correlation is used to represent the degree of matching between current changes and load changes. Specifically, this includes: generating a time series mapping matrix based on the time sampling sequences of the current characteristic trajectory and the load characteristic trajectory, the time series mapping matrix being used to represent the correspondence between the current characteristic trajectory and the load characteristic trajectory in the time dimension; calculating the Euclidean distance between the current characteristic trajectory point and the load characteristic trajectory point at the corresponding time based on the time series mapping matrix to construct a distance calculation matrix, each element in the distance calculation matrix being used to represent the magnitude of the Euclidean distance between the current characteristic trajectory point and the load characteristic trajectory point at the corresponding time; taking the current characteristic trajectory points and load characteristic trajectory points in the distance calculation matrix whose Euclidean distance is less than a preset distance threshold as matching points, and counting the number of matching points; dividing the number of matching points by the total number of logarithms of the current characteristic trajectory points and the load characteristic trajectory points to obtain the correlation.

[0013] By adopting the above technical solution, the monitoring system establishes a time-series mapping matrix, achieving a precise correspondence between current characteristic trajectories and load characteristic trajectories in the time dimension. The monitoring system calculates the Euclidean distance between current characteristic trajectory points and load characteristic trajectory points at corresponding moments to quantitatively assess the degree of matching between current changes and load changes. The monitoring system introduces a preset distance threshold to determine matching points and calculates the correlation by the ratio of the number of matching points to the total number of point pairs, making the evaluation results more objective and reliable, avoiding the subjectivity of traditional experience-based judgments, and improving the accuracy of anomaly detection.

[0014] In conjunction with some embodiments of the first aspect, in some embodiments, the environmental impact coefficient is applied to the correlation to obtain the modified coupling characteristics. Specifically, this includes: establishing a correction function based on the environmental impact coefficient, wherein the correction function decreases as the environmental impact coefficient increases; and substituting the correlation into the correction function to obtain the modified coupling characteristics.

[0015] By adopting the above technical solution, the monitoring system establishes a correction function that decreases as the environmental impact coefficient increases, thus realizing the dynamic correction of environmental factors on the assessment of equipment operating status. This correction mechanism takes into account the adverse effects of ambient temperature and electromagnetic interference on the operation of new energy equipment. By quantitatively applying environmental impact to the correlation through the correction function, a more accurate correction coupling characteristic is obtained, overcoming the limitation of traditional monitoring methods that ignore environmental impact, and making the monitoring results more consistent with actual operating conditions.

[0016] In conjunction with some embodiments of the first aspect, in some embodiments, after determining the device operating state based on the modified coupling characteristics, whereby the device operating state includes safe operation, warning operation, and dangerous operation, the method further includes: when the device operating state is warning operation, calculating the migration probability of the device operating state being dangerous operation; when the migration probability is less than or equal to a preset first migration probability threshold, recording the current state; when the migration probability is greater than the preset first migration probability threshold and less than or equal to a preset second migration probability threshold, adjusting the operating parameters of the new energy device; and when the migration probability is greater than the preset second migration probability threshold, triggering protection measures.

[0017] By adopting the above technical solution, the monitoring system calculates the probability of transitioning from a warning operating state to a dangerous operating state, achieving more refined equipment status management. When the transition probability falls within different ranges, the monitoring system takes corresponding measures, avoiding the abrupt protection in traditional monitoring methods. This ensures equipment safety while reducing unnecessary downtime, making the monitoring system's response more flexible and reasonable.

[0018] In conjunction with some embodiments of the first aspect, in some embodiments, when the migration probability is greater than a preset first migration probability threshold and less than or equal to a preset second migration probability threshold, the operating parameters of the new energy equipment are adjusted, specifically including: determining the current fluctuation amplitude, load change rate, and ambient temperature change rate of the new energy equipment within a preset time period; calculating the deviations of the current fluctuation amplitude, load change rate, and ambient temperature change rate from the corresponding safety thresholds respectively; when the current fluctuation amplitude deviation is the largest, current limiting is performed first; when the load change rate deviation is the largest, load regulation is performed first; when the ambient temperature change rate deviation is the largest, temperature control is performed first.

[0019] By employing the above technical solution, the monitoring system determines the current fluctuation amplitude, load change rate, and ambient temperature change rate within a preset time period. Based on the corresponding safety thresholds, it calculates the deviations, thereby identifying the parameters most in need of adjustment. Depending on the type of the parameter with the largest deviation, the monitoring system prioritizes implementing corresponding control measures: current limiting, load regulation, or temperature control. This differentiated adjustment strategy allows the monitoring system to address the most prominent problems specifically, improving adjustment efficiency and accuracy.

[0020] In a second aspect, embodiments of this application provide a monitoring system comprising: one or more processors and a memory; the memory is coupled to the one or more processors and is used to store computer program code, the computer program code including computer instructions, wherein the one or more processors invoke the computer instructions to cause the monitoring system to perform the method described in the first aspect and any possible implementation thereof.

[0021] Thirdly, embodiments of this application provide a computer program product containing instructions that, when the computer program product is run on a monitoring system, cause the monitoring system to perform the method described in the first aspect and any possible implementation thereof.

[0022] Fourthly, embodiments of this application provide a computer-readable storage medium including instructions that, when executed on a monitoring system, cause the monitoring system to perform the method described in the first aspect and any possible implementation thereof.

[0023] Understandably, the monitoring system provided in the second aspect, the computer program product provided in the third aspect, and the computer storage medium provided in the fourth aspect are all used to execute the methods provided in the embodiments of this application. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods, and will not be repeated here.

[0024] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0025] 1. By adopting the above technical solution, the monitoring system comprehensively analyzes current fluctuation characteristics, load change characteristics, and environmental impact characteristics, constructing a dual-trajectory monitoring model of current characteristic trajectory and load characteristic trajectory. This method not only considers the dynamic change process of current and load, but also calculates the matching degree between current change and load change, and corrects the correlation between current characteristic trajectory and load characteristic trajectory by incorporating the influence of environmental factors. This allows for timely detection of operational anomalies in new energy equipment, making the monitoring results more accurate and reliable. When a dangerous operating state occurs, the monitoring system automatically controls the new energy equipment to stop operating, effectively preventing equipment damage and safety accidents. Compared with traditional single-parameter monitoring methods, this multi-dimensional, dynamic monitoring method has stronger early warning capabilities and higher reliability.

[0026] 2. By adopting the above technical solution, the monitoring system analyzes the periodic characteristics of power consumption patterns to determine periodic load patterns. Combined with the slope of the power curve, it constructs a load characteristic trajectory on a two-dimensional plane, considering both the instantaneous characteristics of load changes (power curve slope) and long-term operational characteristics (periodic load patterns). The monitoring system connects load change characteristic points in chronological order to form a load characteristic trajectory, which can completely record the load change process. This dual-feature analysis method is more advantageous than simply monitoring power changes, and can more accurately reflect the actual operating status of new energy equipment, providing a more reliable basis for equipment anomaly detection.

[0027] 3. By adopting the above technical solution, the monitoring system establishes a time-series mapping matrix, achieving a precise correspondence between current characteristic trajectories and load characteristic trajectories in the time dimension. The monitoring system calculates the Euclidean distance between the current characteristic trajectory points and the load characteristic trajectory points at corresponding moments to quantitatively assess the degree of matching between current changes and load changes. The monitoring system introduces a preset distance threshold to determine matching points and calculates the correlation by the ratio of the number of matching points to the total number of point pairs, making the evaluation results more objective and reliable, avoiding the subjectivity of traditional experience-based judgments, and improving the accuracy of anomaly detection. Attached Figure Description

[0028] Figure 1 This is a flowchart illustrating a dynamic monitoring method for new energy equipment in an embodiment of this application;

[0029] Figure 2 This is another flowchart illustrating the dynamic monitoring method for new energy equipment in this application embodiment;

[0030] Figure 3 This is a schematic diagram of the physical device structure of a monitoring system in an embodiment of this application. Detailed Implementation

[0031] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification of this application, the singular expressions “a,” “an,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to any or all possible combinations including one or more of the listed items.

[0032] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0033] The following describes the process of the method provided in this implementation. Please refer to [link / reference]. Figure 1 This is a flowchart illustrating a dynamic monitoring method for new energy equipment in an embodiment of this application.

[0034] S101. Collect the current fluctuation characteristics, load change characteristics and environmental impact characteristics of new energy equipment. The current fluctuation characteristics include amplitude, frequency and phase. Amplitude refers to the peak value of the current, frequency refers to the periodicity of the current change, and phase refers to the time lead or lag of the current waveform. The load change characteristics include power curve and power consumption mode. The environmental impact characteristics include ambient temperature and electromagnetic interference.

[0035] Among them, new energy equipment refers to equipment that utilizes renewable energy for power generation or energy storage, such as photovoltaic power generation equipment, wind power generation equipment, and energy storage equipment. Current fluctuation characteristics refer to the characteristic parameters of current changes during the operation of new energy equipment, including three dimensions: amplitude, frequency, and phase. Amplitude represents the difference between the maximum and minimum values ​​of the current fluctuation. Frequency represents the number of times the current completes a periodic change per unit time, measured in Hertz (Hz). Phase represents the time difference between the current waveform and the standard reference waveform. Load change characteristics refer to the changes in the electrical load carried by the new energy equipment over time, including power curves and power consumption patterns. The power curve is the curve showing the change in the power of the new energy equipment over time. Power consumption patterns refer to the electricity consumption patterns and characteristics of the new energy equipment. Environmental impact characteristics are used to represent the degree of influence of the external environment on the operation of new energy equipment, including ambient temperature and electromagnetic interference. Ambient temperature refers to the real-time temperature value of the operating environment of the new energy equipment. Electromagnetic interference refers to the degree of interference of external electromagnetic fields on the normal operation of the new energy equipment.

[0036] Specifically, the monitoring system collects real-time current data (current and voltage can be converted to each other, which is not limited here) of the new energy equipment during operation through a built-in current sensor, including the instantaneous value and trend of the current. The monitoring system analyzes the collected real-time current data to extract the amplitude, frequency, and phase of the current. Simultaneously, the monitoring system records the real-time power data of the new energy equipment through a power metering unit, and combines this data with historical data analysis to obtain power curves and power consumption patterns. In addition, the monitoring system also collects ambient temperature data and electromagnetic interference data through temperature sensors and electromagnetic field strength detectors. All collected data is stored in real time by the monitoring system and used for subsequent analysis.

[0037] S102. Based on the amplitude, frequency and phase, construct the current characteristic trajectory. The current characteristic trajectory is used to represent the dynamic change process of current during the operation of new energy equipment.

[0038] The current characteristic trajectory refers to a curve describing the dynamic changes of current in a three-dimensional characteristic space. The three-dimensional characteristic space is a three-dimensional space constructed with amplitude, frequency, and phase as coordinate axes. The dynamic change process of current refers to the continuous change of current parameters over time.

[0039] Specifically, first, the monitoring system standardizes the amplitude, frequency, and phase of the collected current, mapping them to a uniform numerical range. Then, in a three-dimensional feature space, the system uses the standardized feature values ​​at each sampling time as coordinates to generate corresponding current feature points. The system connects these current feature points in chronological order to form the original current trajectory. Next, the system calculates the geometric features of the original current trajectory, including the curvature at each current feature point, the cumulative trajectory length, and the direction of the trajectory tangent vector. Finally, the system constructs a feature space model based on these geometric features, serving as the final current feature trajectory.

[0040] Optionally, in general, the current characteristic trajectory can be constructed based on amplitude, frequency, and phase in the following ways, without limitation: map amplitude, frequency, and phase in a three-dimensional coordinate system to obtain current characteristic points; perform time-series connection of current characteristic points to obtain the original current trajectory; calculate the current characteristic vector based on the original current trajectory, the current characteristic vector including trajectory curvature, trajectory length, and trajectory direction; establish a feature space model based on the current characteristic vector, and use the feature space model as the current characteristic trajectory.

[0041] Here, a current feature point refers to a mapping point of the current characteristic at a certain moment in a three-dimensional feature space. The original current trajectory refers to the spatial curve formed by connecting the time-series current feature points. The current feature vector is used to represent the geometric characteristics of the current feature trajectory, including three dimensions: trajectory curvature, trajectory length, and trajectory direction.

[0042] Assume the monitoring system collects the following current data at five consecutive time points:

[0043] Time t1: Amplitude = 100A, Frequency = 50Hz, Phase = 0°;

[0044] Time t2: Amplitude = 120A, Frequency = 49.8Hz, Phase = 5°;

[0045] Time t3: Amplitude = 150A, Frequency = 49.5Hz, Phase = 15°;

[0046] Time t4: Amplitude = 130A, Frequency = 49.7Hz, Phase = 10°;

[0047] Time t5: Amplitude = 95A, Frequency = 50.1Hz, Phase = -5°.

[0048] Standardization (assuming standardization to the [0, 1] interval):

[0049] t1: (0.4, 0.5, 0.5)→P1;

[0050] t2: (0.5, 0.48, 0.55)→P2;

[0051] t3: (0.7, 0.45, 0.65)→P3;

[0052] t4: (0.55, 0.47, 0.6)→P4;

[0053] t5: (0.35, 0.51, 0.45)→P5.

[0054] Current feature point generation: Each standardized data point forms a point in the three-dimensional feature space, with coordinate values ​​of (amplitude, frequency, phase).

[0055] Original current trajectory: Connect P1→P2→P3→P4→P5 in sequence to form a spatial curve.

[0056] Computational geometric characteristics: (1) The curvature of the trajectory is the largest at P3, indicating that the current parameter changes most drastically here; (2) The total length of the trajectory is approximately 0.8 units; (3) The trajectory direction generally shows a trend of first rising and then falling.

[0057] Feature space model: Based on the above geometric features, the characteristics of the current trajectory during this period can be obtained: the amplitude of the current went through a process of first increasing and then decreasing, the frequency fluctuated slightly but remained basically stable, and the phase had a significant fluctuation process, with a large fluctuation at time t3 (point P3), which needs to be paid close attention to.

[0058] This current characteristic trajectory reflects that the new energy equipment may have experienced a sudden load change (at time t3) during this period, but its overall operating status remained basically stable. Through the analysis of this three-dimensional characteristic trajectory, the timing and extent of abnormal current changes can be intuitively identified.

[0059] S103. Extract the slope of the power curve and the periodicity of the power consumption pattern from the load change characteristics to construct the load characteristic trajectory, which is used to represent the dynamic load change process when the new energy equipment is running.

[0060] Among them, the slope of the power curve refers to the rate at which the load changes over time during the operation of new energy equipment. The periodicity of the electricity consumption pattern refers to the repetitive pattern of load changes. The load characteristic trajectory is used to represent the dynamic trajectory of the load changing over time during the operation of new energy equipment.

[0061] Specifically, firstly, the monitoring system performs numerical differentiation on the power curve to calculate the rate of power change at each moment, i.e., the slope of the power curve. Simultaneously, the system uses methods such as Fourier analysis to perform periodic analysis on historical load data, extracting the main periodic components and determining standard periodic load patterns. Then, on a two-dimensional feature plane, the system uses the power curve slope as the abscissa and the similarity to the periodic load pattern as the ordinate to generate load change feature points. Finally, the system connects these load change feature points in chronological order to form a complete load feature trajectory, used to characterize the dynamic change process of the load on new energy equipment.

[0062] Optionally, in general, extracting the power curve slope and electricity consumption pattern periodicity from load change characteristics to construct a load characteristic trajectory can be achieved in the following ways, without limitation: determine the periodic load pattern based on the electricity consumption pattern periodicity; map the power curve slope and the periodic load pattern on a two-dimensional plane to generate load change feature points; connect the load change feature points in chronological order to obtain the load characteristic trajectory.

[0063] Here, a periodic load pattern refers to a standard load variation pattern within a complete cycle. A load variation characteristic point is a point on a two-dimensional plane that maps the load characteristics at a given moment. The load characteristic trajectory represents the dynamic trajectory of the load of new energy equipment over time. The two-dimensional plane is a characteristic plane constructed using the slope of the power curve and the periodic load pattern as coordinate axes.

[0064] Suppose the monitoring system records the power data of a photovoltaic power generation device over 24 hours:

[0065] 00:00-20kW;

[0066] 04:00-15kW;

[0067] 08:00-45kW;

[0068] 12:00-90kW;

[0069] 16:00-50kW;

[0070] 20:00-25kW.

[0071] Calculate the slope of the power curve (one sampling point every 4 hours):

[0072] Time period 1 (00:00-04:00): (-5kW) / (4h) = -1.25kW / h;

[0073] Time period 2 (04:00-08:00): (+30kW) / (4h) = +7.5kW / h;

[0074] Time period 3 (08:00-12:00): (+45kW) / (4h)=+11.25kW / h;

[0075] Period 4 (12:00-16:00): (-40kW) / (4h) = -10kW / h;

[0076] Time period 5 (16:00-20:00): (-25kW) / (4h)=-6.25kW / h.

[0077] Periodic analysis: Fourier analysis revealed that the photovoltaic power generation equipment has obvious 24-hour periodic characteristics, that is, the standard periodic pattern is low in the early morning → rise in the morning → peak at noon → decline in the evening.

[0078] Similarity between the current time period and the standard pattern:

[0079] Time period 1: 0.95 (perfect for night mode);

[0080] Period 2: 0.90 (consistent with the morning upward pattern);

[0081] Period 3: 0.92 (consistent with the daytime upward trend);

[0082] Period 4: 0.88 (consistent with the afternoon decline pattern);

[0083] Period 5: 0.85 (basically in line with the evening descent pattern).

[0084] Generate load change feature points:

[0085] The coordinates of the mapped point on the two-dimensional plane are (slope of the power curve, similarity):

[0086] P1: (-1.25, 0.95);

[0087] P2: (7.5, 0.90);

[0088] P3: (11.25, 0.92);

[0089] P4: (-10, 0.88);

[0090] P5: (-6.25, 0.85).

[0091] Constructing the load characteristic trajectory: Connecting P1→P2→P3→P4→P5 in time sequence, the resulting load characteristic trajectory shows that the load characteristic trajectory in the first quadrant (positive slope, high similarity) represents the normal load growth stage, and the load characteristic trajectory in the fourth quadrant (negative slope, high similarity) represents the normal load decline stage. The load characteristic trajectory as a whole moves in a clockwise direction, which is consistent with the daily pattern of solar power generation.

[0092] Analysis conclusion: The load change of the photovoltaic power generation equipment conforms to the typical characteristics of photovoltaic power generation. The maximum power change rate occurs between 8:00 am and 12:00 pm (+11.25 kW / h). The overall similarity remains above 0.85, indicating that the operating status is stable and there are no abnormal load changes or cycle deviations.

[0093] This example demonstrates how to construct load characteristic trajectories by analyzing power change rate and periodic characteristics, thereby assessing the operating status of new energy equipment, which is particularly suitable for monitoring new energy equipment with obvious periodic characteristics.

[0094] S104. Based on ambient temperature and electromagnetic interference, determine the environmental impact coefficient. The environmental impact coefficient is used to represent the intensity of the impact of ambient temperature and electromagnetic interference on the operation of new energy equipment.

[0095] Among them, the environmental impact coefficient refers to the overall degree of impact of environmental factors on the operation of new energy equipment. The impact intensity refers to the degree to which environmental factors inhibit the performance of new energy equipment.

[0096] Specifically, firstly, the monitoring system compares the measured ambient temperature with an ambient temperature threshold to calculate the temperature deviation. The ambient temperature threshold refers to the highest and lowest ambient temperatures allowed for the normal operation of the new energy equipment. Simultaneously, the monitoring system calculates the ratio of the measured electromagnetic interference intensity to the electromagnetic interference threshold, obtaining the electromagnetic interference level. The electromagnetic interference threshold refers to the maximum electromagnetic interference intensity that the new energy equipment can withstand. Based on the characteristics of the new energy equipment, the monitoring system pre-sets temperature influence weights and electromagnetic interference weights, multiplying the temperature deviation and electromagnetic interference level by their respective weights. The temperature influence weight represents the importance of temperature in the environmental impact, and the electromagnetic interference weight represents the importance of electromagnetic interference. Finally, the monitoring system adds the two weighted results, normalizes them, and obtains the final environmental impact coefficient. The larger this environmental impact coefficient, the stronger the adverse impact of environmental factors on the operation of the new energy equipment.

[0097] S105. Compare the current characteristic trajectory and the load characteristic trajectory in time series and calculate the correlation. The correlation is used to represent the degree of matching between the current change and the load change.

[0098] Among them, time-series comparison refers to the process of synchronously comparing the current characteristic trajectory and the load characteristic trajectory in the time dimension; correlation indicates the degree of consistency between the changing trends of the current characteristic trajectory and the load characteristic trajectory, and its value ranges from 0 to 1. The larger the value, the higher the degree of matching; the degree of matching is used to indicate whether the current change is adapted to the load change, reflecting the coordination of equipment operation.

[0099] Specifically, firstly, the monitoring system establishes a time-series mapping matrix to align the current characteristic trajectory and the load characteristic trajectory on the time axis. Then, the system calculates the Euclidean distance between the current characteristic trajectory points and the load characteristic trajectory points at corresponding time points, constructing a distance calculation matrix. Next, the system determines a preset distance threshold and counts the number of matching points whose Euclidean distance is less than the preset threshold. Finally, the system divides the number of matching points by the total logarithm to obtain the correlation coefficient, reflecting the overall degree of matching. This correlation coefficient calculation method based on time-series comparison can accurately reflect the coordination between current changes and load changes during the operation of new energy equipment.

[0100] Optionally, in general, comparing the current characteristic trajectory and the load characteristic trajectory in time series and calculating the correlation, the correlation is used to represent the degree of matching between current changes and load changes. This can be achieved in the following ways, without limitation: Generate a time-series mapping matrix based on the time sampling sequences of the current characteristic trajectory and the load characteristic trajectory. The time-series mapping matrix represents the correspondence between the current characteristic trajectory and the load characteristic trajectory in the time dimension. Based on the time-series mapping matrix, calculate the Euclidean distance between the current characteristic trajectory points and the load characteristic trajectory points at corresponding times to construct a distance calculation matrix. Each element in the distance calculation matrix represents the magnitude of the Euclidean distance between the current characteristic trajectory points and the load characteristic trajectory points at corresponding times. Current characteristic trajectory points and load characteristic trajectory points whose Euclidean distance in the distance calculation matrix is ​​less than a preset distance threshold are taken as matching points, and the number of matching points is counted. The number of matching points is divided by the total number of logarithms of the current characteristic trajectory points and the load characteristic trajectory points to obtain the correlation.

[0101] Assume data is collected at 5 consecutive time points:

[0102] Current characteristic trajectory points (three-dimensional spatial coordinates, standardized):

[0103] t1: E1(0.4, 0.5, 0.3);

[0104] t2: E2(0.5, 0.5, 0.4);

[0105] t3: E3(0.7, 0.4, 0.6);

[0106] t4: E4(0.6, 0.4, 0.5);

[0107] t5: E5(0.4, 0.5, 0.3).

[0108] Load characteristic trajectory points (two-dimensional plane coordinates, standardized):

[0109] t1: L1(0.3, 0.5);

[0110] t2: L2(0.4, 0.5);

[0111] t3: L3(0.6, 0.4);

[0112] t4: L4(0.5, 0.4);

[0113] t5: L5(0.3, 0.5).

[0114] Calculation process:

[0115] Construct a time-series mapping matrix (a 5×5 matrix, where 1 indicates a time correspondence and 0 indicates no correspondence):

[0116] L1 L2 L3 L4 L5 E1 1 0 0 0 0 E2 0 1 0 0 0 E3 0 0 1 0 0 E4 0 0 0 1 0 E5 0 0 0 0 1

[0117] Calculate the Euclidean distance (for ease of calculation, the three-dimensional current characteristics are projected onto a two-dimensional plane): d1=√[(0.4-0.3)2+(0.5-0.5)2]=0.1;

[0118] d2=√[(0.5-0.4)2+(0.5-0.5)2]=0.1;

[0119] d3=√[(0.7-0.6)2+(0.4-0.4)2]=0.1;

[0120] d4=√[(0.6-0.5)2+(0.4-0.4)2]=0.1;

[0121] d5=√[(0.4-0.3)2+(0.5-0.5)2]=0.1.

[0122] Construct the distance calculation matrix:

[0123]

[0124]

[0125] Assuming the preset distance threshold is 0.15, the number of matching points is 5, and the total number of pairs is 5.

[0126] Calculate the relevance: Relevance = Number of matching points / Total number of pairs = 5 / 5 = 1.0.

[0127] Results analysis: The obtained correlation is 1.0, which indicates that the current change and the load change are highly matched. The Euclidean distance between the current characteristic point and the load characteristic point at each moment is very small, indicating that the change trend is consistent. The perfect correlation indicates that the operation of the new energy equipment is very coordinated and the current response is synchronized with the load change.

[0128] S106. Apply the environmental impact coefficient to the correlation to obtain the modified coupling characteristics;

[0129] Among them, the modified coupling characteristic refers to the current-load matching characteristic after being corrected for environmental factors, which is an indicator that comprehensively reflects the operating status of new energy equipment; the action process refers to the mathematical calculation process that incorporates environmental impact factors through a specific correction function.

[0130] Specifically, firstly, the monitoring system constructs a correction function based on the environmental impact coefficient. This correction function decreases as the environmental impact coefficient increases, typically using an exponential decay method. Then, the monitoring system substitutes the correlation coefficient into the correction function for calculation, obtaining the corrected coupling characteristics after considering the environmental impact. This correction mechanism can reasonably reflect the impact of environmental factors on the operating status of new energy equipment, making the assessment results more accurate and reliable.

[0131] Example: Assume the environmental impact factor (E) is 0.58 and the correlation (R) is 0.95 (indicating a high current-load matching degree). The correction function is f(E) = e^(-kE), where k is the attenuation coefficient.

[0132] Assuming k = 1, the correction coefficient = e^(-1 × 0.58) = e^(-0.58) = 0.56, and the corrected coupling characteristic = correlation × correction coefficient = 0.95 × 0.56 = 0.532.

[0133] Optionally, under normal circumstances, applying the environmental impact coefficient to the correlation to obtain the modified coupling characteristics can be achieved in the following ways, without limitation: establish a correction function based on the environmental impact coefficient, the correction function decreasing as the environmental impact coefficient increases; substitute the correlation into the correction function to obtain the modified coupling characteristics.

[0134] Correction effects under different environmental conditions:

[0135] Scene comparison analysis:

[0136] (1) Ideal environmental conditions:

[0137] Environmental impact coefficient = 0.1;

[0138] Correction factor = e^(-0.1) = 0.905;

[0139] Relevance = 0.95;

[0140] Corrected coupling characteristic = 0.95 × 0.905 = 0.860;

[0141] (2) Moderate environmental impact (current situation):

[0142] Environmental impact coefficient = 0.58;

[0143] Correction factor = e^(-0.58) = 0.56;

[0144] Relevance = 0.95;

[0145] Corrected coupling characteristic = 0.95 × 0.56 = 0.532;

[0146] (3) Harsh environmental conditions:

[0147] Environmental impact coefficient = 0.9;

[0148] Correction factor = e^(-0.9) = 0.407;

[0149] Relevance = 0.95;

[0150] Corrected coupling characteristic = 0.95 × 0.407 = 0.387;

[0151] Results analysis: The original correlation coefficient of 0.95 indicates that the current-load matching of the new energy equipment is very good. The environmental impact coefficient of 0.58 leads to the correction coefficient being reduced to 0.56. The final corrected coupling characteristic is 0.532, which is significantly lower than the original correlation coefficient, indicating that environmental factors have a significant adverse impact on the operation of new energy equipment.

[0152] S107. Determine the equipment operating status based on the modified coupling characteristics. The equipment operating status includes safe operation, early warning operation, and dangerous operation.

[0153] Among them, safe operation refers to the state in which the equipment is working within the normal parameter range; early warning operation refers to the state in which the equipment has a minor abnormality but can still continue to operate; dangerous operation refers to the state in which the equipment has a serious abnormality and needs to be dealt with immediately.

[0154] Specifically, the monitoring system sets two thresholds to divide the range of values ​​for the modified coupling characteristics into three intervals, corresponding to three operating states: above the first threshold is safe operation, between the two thresholds is warning operation, and below the second threshold is dangerous operation. These thresholds are usually determined based on historical operating data and expert experience, and can be dynamically adjusted according to actual operating conditions.

[0155] S108. When the equipment is in a dangerous operating state, control the new energy equipment to stop operating.

[0156] Stopping operation refers to putting the new energy equipment into a safe shutdown state through control commands; control commands include emergency shutdown signals, power reduction commands, etc.; safe shutdown state refers to a non-working state in which all parameters of the new energy equipment are within safe ranges.

[0157] Specifically, first, the monitoring system confirms that the equipment is operating in a dangerous state. Then, the monitoring system generates a sequence of shutdown control commands, which includes a series of ordered control commands such as current cutoff, load unloading, and protection circuit activation. Next, the monitoring system sends these shutdown control commands to the equipment execution unit in a predetermined order, ensuring that the new energy equipment enters a shutdown state according to a safe procedure.

[0158] By adopting the above technical solution, the monitoring system comprehensively analyzes current fluctuation characteristics, load change characteristics, and environmental impact characteristics, constructing a dual-trajectory monitoring model of current characteristic trajectory and load characteristic trajectory. This method not only considers the dynamic changes in current and load but also calculates the matching degree between current and load changes. Furthermore, it incorporates the influence of environmental factors to correct the correlation between the current and load characteristic trajectories, thereby promptly detecting operational anomalies in new energy equipment and making the monitoring results more accurate and reliable. When a dangerous operating state occurs, the monitoring system automatically controls the new energy equipment to stop operating, effectively preventing equipment damage and safety accidents. Compared to traditional single-parameter monitoring methods, this multi-dimensional, dynamic monitoring method has stronger early warning capabilities and higher reliability.

[0159] The following provides a more detailed description of the process of the method provided in this implementation. Please refer to [link / reference]. Figure 2 This is another flowchart illustrating the dynamic monitoring method for new energy equipment in this application.

[0160] The following steps may or may not be performed after step S107; this is not limited here:

[0161] S201. When the equipment is in a warning operation state, calculate the probability of the equipment transitioning to a dangerous operation state.

[0162] Warning operation refers to a state where the operating status of new energy equipment has potential risks but has not yet reached a dangerous level. Dangerous operation refers to a state where the operating status of new energy equipment has shown obvious abnormalities, which may lead to equipment failure or safety accidents. The transition probability is used to represent the likelihood of the equipment's operating status changing from one state to another, and its value ranges from 0 to 1.

[0163] Specifically, firstly, the monitoring system collects current operational data of the new energy equipment, including key indicators such as corrected coupling characteristics and environmental impact coefficients. Then, based on historical data and current operating parameters, the monitoring system calculates the probability of the new energy equipment transitioning from a warning operating state to a dangerous operating state under existing conditions. This probability calculation typically employs a Bayesian probability model or a Markov chain model, comprehensively considering the historical state transition patterns of the new energy equipment, the degree of anomaly in current operating parameters, and the influence of environmental factors.

[0164] S202. When the migration probability is less than or equal to the preset first migration probability threshold, record the current state;

[0165] Here, the preset first migration probability threshold refers to a pre-set, relatively low migration probability judgment standard. The current state refers to the set of operating parameters and performance indicators of the new energy equipment at this very moment.

[0166] Specifically, if the migration probability is less than or equal to the preset first migration probability threshold, it indicates that the risk of equipment condition deterioration is relatively low. At this time, the monitoring system will fully record the current status of the new energy equipment, including but not limited to: corrected coupling characteristics, environmental impact coefficient, various operating parameters, timestamps and other key data, for subsequent trend analysis and predictive maintenance.

[0167] S203. When the migration probability is greater than the preset first migration probability threshold and less than or equal to the preset second migration probability threshold, adjust the operating parameters of the new energy equipment.

[0168] The preset second migration probability threshold is a higher judgment standard than the first migration probability threshold, used to distinguish between the state where parameters need to be adjusted and the state where protection needs to be activated.

[0169] Specifically, firstly, the monitoring system collects and calculates three key indicators—current fluctuation amplitude, load change rate, and ambient temperature change rate—within a preset time period (e.g., 15 minutes). Then, the system compares these indicators with their respective safety thresholds to calculate the deviation values. Based on the parameter type corresponding to the maximum deviation value, an appropriate adjustment strategy is selected: when the current fluctuation deviation is the largest, the current is limited by reducing output power or adjusting the operating mode; when the load change deviation is the largest, operation is stabilized by adjusting load distribution or reducing the load level; when the temperature change deviation is the largest, temperature control is strengthened or heat dissipation measures are adjusted. This maximum deviation-based priority adjustment strategy effectively reduces equipment operation risks.

[0170] Optionally, under normal circumstances, when the migration probability is greater than a preset first migration probability threshold and less than or equal to a preset second migration probability threshold, the operating parameters of the new energy equipment can be adjusted in the following ways, without limitation: determine the current fluctuation amplitude, load change rate, and ambient temperature change rate of the new energy equipment within a preset time period; calculate the deviations of the current fluctuation amplitude, load change rate, and ambient temperature change rate from the corresponding safety thresholds respectively; when the deviation of the current fluctuation amplitude is the largest, current limiting is executed first; when the deviation of the load change rate is the largest, load regulation is executed first; when the deviation of the ambient temperature change rate is the largest, temperature control is executed first.

[0171] Among these, current fluctuation amplitude refers to the range of current value changes during the operation of new energy equipment. Load change rate refers to the degree of change in the load of new energy equipment per unit time. Ambient temperature change rate refers to the rate of change of ambient temperature per unit time. Safety threshold refers to the maximum allowable range of change for each operating parameter. Deviation is used to indicate the degree of difference between the actual value and the safety threshold.

[0172] S204. When the migration probability is greater than the preset second migration probability threshold, the protection measures are triggered.

[0173] The preset second migration probability threshold refers to the pre-set highest migration probability judgment standard. Protective measures refer to emergency protective actions taken to prevent serious equipment failures or safety accidents. Trigger indicates the initiation or execution of the corresponding protective operation.

[0174] Specifically, the monitoring system immediately activates protective measures, which may include: emergency load reduction or shutdown, disconnection of dangerous circuits, activation of backup systems, and issuance of alarm signals. Simultaneously, the monitoring system records complete status information when the protective measures are triggered, including various parameter data, alarm information, and operation logs, providing a basis for subsequent analysis and processing. This timely protection can minimize the risk of serious equipment failures or safety accidents.

[0175] The monitoring system in the embodiments of this invention is described below from the perspective of hardware processing. Please refer to [link / reference needed]. Figure 3 This is a schematic diagram of the physical device structure of the monitoring system in this application embodiment.

[0176] It should be noted that, Figure 3 The structure of the monitoring system shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0177] like Figure 3 As shown, the monitoring system includes a CPU 301, which can perform various appropriate actions and processes based on a program stored in the read-only memory ROM 302 or a program loaded from the storage section 308 into the random access memory RAM 303, such as performing the methods described in the above embodiments. The RAM 303 also stores various programs and data required for system operation. The CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An I / O interface 305 is also connected to the bus 304.

[0178] The following components are connected to I / O interface 305: input section 306 including audio input devices, push-button switches, etc.; output section 307 including a liquid crystal display (LCD) and audio output devices, indicator lights, etc.; storage section 308 including a hard disk, etc.; and communication section 309 including a network interface card such as a LAN (Local Area Network) card, modem, etc. Communication section 309 performs communication processing via a network such as the Internet. Drive 310 is also connected to I / O interface 305 as needed. Removable media 311, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 310 as needed so that computer programs read from them can be installed into storage section 308 as needed.

[0179] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing computer programs for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 309, and / or installed from removable medium 311. When the computer program is executed by CPU 301, it performs the various functions defined in the present invention.

[0180] It should be noted that specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0181] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. Each block in a flowchart or block diagram may represent a module, program segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those shown in the drawings.

[0182] Specifically, the monitoring system in this embodiment includes a processor and a memory. The memory stores a computer program, and when the computer program is executed by the processor, it implements the dynamic monitoring method for new energy equipment provided in the above embodiment.

[0183] In another aspect, the present invention also provides a computer-readable storage medium, which may be included in the monitoring system described in the above embodiments; or it may exist independently and not be assembled into the monitoring system. The storage medium carries one or more computer programs, which, when executed by a processor of the monitoring system, enable the monitoring system to implement the dynamic monitoring method for new energy equipment provided in the above embodiments.

[0184] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

[0185] As used in the above embodiments, depending on the context, the term "when..." can be interpreted as meaning "if...", "after...", "in response to determining...", or "in response to detecting...". Similarly, depending on the context, the phrase "when determining..." or "if (the stated condition or event) is interpreted as meaning "if determining...", "in response to determining...", "when (the stated condition or event) is detected", or "in response to detecting (the stated condition or event)".

[0186] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This program can be stored in a computer-readable storage medium, and when executed, it can include the processes described in the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A new energy equipment dynamic monitoring method, characterized in that, The method is applied to a monitoring system and comprises the following steps: collecting current fluctuation characteristics, load change characteristics and environmental influence characteristics of a new energy device, wherein the current fluctuation characteristics comprise amplitude, frequency and phase, the amplitude refers to the peak value of current size, the frequency refers to the periodicity of current change, and the phase refers to the time advance or lag of current waveform, the load change characteristics comprise power curve and power consumption mode, and the environmental influence characteristics comprise environmental temperature and electromagnetic interference; constructing a current characteristic track according to the amplitude, the frequency and the phase, wherein the current characteristic track is used to represent the dynamic change process of current when the new energy device is running; extracting the power curve slope and the periodicity of power consumption mode from the load change characteristics to construct a load characteristic track, wherein the load characteristic track is used to represent the dynamic change process of load when the new energy device is running; determining an environmental influence coefficient based on the environmental temperature and the electromagnetic interference, wherein the environmental influence coefficient is used to represent the influence intensity of the environmental temperature and the electromagnetic interference on the running of the new energy device; performing time sequence comparison on the current characteristic track and the load characteristic track to calculate a correlation degree, wherein the correlation degree is used to represent the matching degree of current change and load change; applying the environmental influence coefficient to the correlation degree to obtain a modified coupling characteristic; determining a device running state based on the modified coupling characteristic, wherein the device running state comprises safe running, early warning running and dangerous running; and stopping the new energy device from running when the device running state is the dangerous running. The application of the environmental influence coefficient to the correlation degree to obtain the modified coupling characteristic specifically comprises the following steps: establishing a correction function according to the environmental influence coefficient, wherein the correction function decreases with the increase of the environmental influence coefficient; and substituting the correlation degree into the correction function to obtain the modified coupling characteristic. The monitoring system compares the measured environmental temperature with an environmental temperature threshold to calculate a temperature deviation degree, wherein the environmental temperature threshold refers to the maximum and minimum environmental temperatures allowed for the normal running of the new energy device; the monitoring system calculates the ratio of the measured electromagnetic interference intensity to an electromagnetic interference threshold to obtain an electromagnetic interference degree, wherein the electromagnetic interference threshold refers to the maximum electromagnetic interference intensity that can be borne by the new energy device; the monitoring system pre-sets a temperature influence weight and an electromagnetic interference weight according to the characteristics of the new energy device, multiplies the temperature deviation degree and the electromagnetic interference degree by the corresponding weights respectively, wherein the temperature influence weight is used to represent the importance of temperature factors in environmental influence, and the electromagnetic interference weight is used to represent the importance of electromagnetic interference in environmental influence; and the monitoring system adds the two weighted results to obtain the final environmental influence coefficient after normalization processing, wherein the greater the environmental influence coefficient is, the stronger the adverse influence of environmental factors on the running of the new energy device is. The monitoring system sets two thresholds to divide the value range of the modified coupling feature into three intervals, which correspond to three operating states respectively: higher than the first threshold is safe operation, between the two thresholds is pre-warning operation, and lower than the second threshold is dangerous operation; these thresholds are determined based on historical operation data and expert experience, and can be dynamically adjusted according to actual operation conditions.

2. The method of claim 1, wherein, The method further comprises: mapping the amplitude, the frequency and the phase in a three-dimensional coordinate system to obtain a current feature point; connecting the current feature points in time sequence to obtain an original current trajectory; calculating a current feature vector based on the original current trajectory, the current feature vector including a trajectory curvature, a trajectory length and a trajectory direction; and establishing a feature space model according to the current feature vector, and taking the feature space model as the current feature trajectory.

3. The method of claim 1, wherein, The method further comprises: determining a periodic load mode according to the power curve slope and the periodicity of the power consumption mode; mapping the power curve slope and the periodic load mode on a two-dimensional plane to generate a load change feature point; and connecting the load change feature points in time sequence to obtain the load feature trajectory.

4. The method of claim 1, wherein, The method further comprises: generating a time sequence mapping matrix according to the time sampling sequence of the current feature trajectory and the time sampling sequence of the load feature trajectory, the time sequence mapping matrix being used to represent the corresponding relationship of the current feature trajectory and the load feature trajectory in the time dimension; calculating the Euclidean distance between the current feature trajectory points and the load feature trajectory points at the corresponding time based on the time sequence mapping matrix to construct a distance calculation matrix, each element in the distance calculation matrix being used to represent the Euclidean distance between the current feature trajectory points and the load feature trajectory points at the corresponding time; taking the current feature trajectory points and the load feature trajectory points with the Euclidean distance less than a preset distance threshold in the distance calculation matrix as matching points, and counting the number of matching points; and dividing the number of matching points by the total number of current feature trajectory points and load feature trajectory points to obtain the correlation degree.

5. The method of claim 1, wherein, After the step of determining the device operating state based on the modified coupling feature, the device operating state including safe operation, pre-warning operation and dangerous operation, the method further comprises: when the device operating state is the pre-warning operation, calculating a migration probability of the device operating state being the dangerous operation; when the migration probability is less than or equal to a preset first migration probability threshold, recording the current state; when the migration probability is greater than the preset first migration probability threshold and less than or equal to a preset second migration probability threshold, adjusting the operating parameters of the new energy device; and when the migration probability is greater than the preset second migration probability threshold, triggering a protection measure.

6. The method of claim 5, wherein, The adjusting the operation parameter of the new energy equipment when the migration probability is greater than the preset first migration probability threshold and less than or equal to a preset second migration probability threshold specifically comprises: determining current fluctuation amplitude, load change rate and environmental temperature change rate of the new energy equipment within a preset time length; calculating the deviation of the current fluctuation amplitude, the load change rate and the environmental temperature change rate from the corresponding safety threshold respectively; when the current fluctuation amplitude deviation is the largest, preferentially performing current limiting; when the load change rate deviation is the largest, preferentially performing load adjustment; when the environmental temperature change rate deviation is the largest, preferentially performing temperature control.

7. A monitoring system, characterized by The monitoring system comprises one or more processors and a memory; the memory is coupled with the one or more processors, the memory is used to store computer program code, the computer program code comprises computer instructions, and the one or more processors invoke the computer instructions to enable the monitoring system to perform the method in any one of claims 1 to 6.

8. A computer-readable storage medium comprising instructions, characterized in that, The instructions enable the monitoring system to perform the method in any one of claims 1 to 6 when the instructions run on the monitoring system.

9. A computer program product, characterised in that, The computer program product enables the monitoring system to perform the method in any one of claims 1 to 6 when the computer program product runs on the monitoring system.

Images