New energy station operation state dynamic monitoring and emergency takeover method and system

Abstract

The invention discloses a new energy station operation state dynamic monitoring and emergency takeover method and system. The method comprises the steps that operation state parameters of a charging pile at a current detection point are detected in real time; obtaining each operation state parameter in real time; constructing a state analysis model, inputting each operation state parameter, and outputting the overall operation state parameter of the station; comparing the overall operation state parameter with a threshold value in real time, and judging whether the operation state of the station is normal or not; and when the operation state of the station is abnormal, emergency takeover is completed, emergency weak current of the current station is implemented, and the charging current is reduced to 1 / L of the original. According to the invention, a charging pile real-time monitoring network is constructed based on the temperature sensor and the characteristic model, so that three-dimensional dynamic sensing of the temperature change rate, peak value and slope of the charging port is realized; and the coupling effect of the adjacent charging piles is quantified through a formula, so that the comprehensive state evaluation error rate of the station is reduced to 4.8%.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent monitoring of new energy power stations, and particularly to a method and system for dynamically monitoring the operating state and emergency takeover of new energy power stations, which is applicable to the intelligent operation and maintenance management of new energy facilities in energy storage power stations. Background Art

[0002] Under the background of the global energy transformation, as an important supply node of clean energy, the safe, efficient and stable operation of new energy power stations is crucial for the sustainable development of energy. With the continuous progress and popularization of new energy technologies, the scale of new energy power stations is expanding day by day, and the number of charging facilities has also increased sharply. In this context, accurately monitoring the operating state of new energy power stations has become a key link to ensure their stable operation.

[0003] Currently, many obvious defects have emerged in the actual application of existing new energy power station operating state monitoring technologies. From the perspective of system design, the monitoring system does not comprehensively consider the interaction effects among the charging points in the power station. The charging points in a new energy power station do not exist in isolation, and there are complex interactions among them in terms of stable and safe operation. For example, when the charging power of a certain charging point suddenly increases and the temperature of its charging port rises abnormally, it will affect the stable and safe operation of the surrounding charging points, and may even lead to the imbalance of the entire power station. However, existing monitoring systems often regard each charging point as an independent entity for monitoring, ignoring this potential interaction effect, resulting in the monitoring results being unable to fully reflect the true operating state of the power station, leading to insufficient accuracy in the comprehensive state assessment of the power station and being unable to adapt to the dynamic operating environment of new energy power stations. Summary of the Invention

[0004] The purpose of this part is to outline some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this part, as well as in the abstract and title of the specification of this application, to avoid obscuring the purpose of this part, the abstract, and the title. However, such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] In view of the problems existing in the above-mentioned existing new energy power station operating state monitoring technologies, the present invention is proposed.

[0006] Therefore, the technical problem solved by the present invention is to solve the problem that the existing new energy power station operating state monitoring system does not comprehensively consider the interaction effects among the charging points in the power station, and the single direct assessment method adopted leads to insufficient accuracy in the comprehensive state assessment of the power station and being unable to adapt to the dynamic operating environment of new energy power stations.

[0007] To solve the above technical problems, the present invention provides the following technical solutions: A method for dynamically monitoring the operating status and emergency takeover of a new energy power station. Detection units are installed on all charging piles configured in the new energy power station, including the following steps: S1: The detection unit continuously detects the operating status parameter A of the charging pile at the current detection point; S2: The statistical module is wirelessly connected to each detection unit to continuously obtain each operating status parameter A; S3: A status analysis model is constructed through an analysis module embedded in the statistical module, and each operating status parameter A is input to output the overall operating status parameter A of the power station 综 ; S4: The comparison module continuously compares the overall operating status parameter A 综 with the threshold value to determine whether the operating status of the power station is normal; S5: When the operating status of the power station is abnormal, the emergency takeover module completes the emergency takeover, and the internal control unit implements the emergency weak power of the current power station to reduce the charging current to 1 / L of the original.

[0008] As a preferred solution of the method for dynamically monitoring the operating status and emergency takeover of the new energy power station described in the present invention, wherein: The detection unit is specifically a temperature sensor, which is arranged at the charging port to continuously detect the temperature value at the contact between the charging port and the vehicle charging end.

[0009] As a preferred solution of the method for dynamically monitoring the operating status and emergency takeover of the new energy power station described in the present invention, wherein: In step S1, detecting the operating status parameter A of the charging pile at the current detection point specifically includes the following steps: H1: At the beginning of charging, the detection unit continuously obtains the change in the temperature of the charging port; H2: A time-temperature change curve is formed; H3: The curve characteristic value is obtained; H4: The obtained curve characteristic value is input into a preset characteristic model to output the corresponding operating status parameter A.

[0010] As a preferred solution of the method for dynamically monitoring the operating status and emergency takeover of the new energy power station described in the present invention, wherein: The characteristic model is specifically:

[0011] wherein, A is the operating status parameter; T max is the ordinate at the highest temperature point in the time-temperature change curve, °C; T kmax is the ordinate at the point with the maximum change slope in the time-temperature change curve, °C; t Tmax is the abscissa at the highest temperature point in the time-temperature change curve, s; t kmax is the abscissa at the point with the maximum change slope in the time-temperature change curve, s; ln2.1 is the adjustment constant.

[0012] As a preferred solution of the method for dynamically monitoring the operation status and emergency takeover of a new energy power station according to the present invention, wherein: the status analysis model in step S3 is specifically:

[0013] Among them, A 综 is the overall operation status parameter; A1 is the operation status parameter of the charging pile at the first detection point; A n is the operation status parameter of the charging pile at the nth detection point; n is the number of charging piles at the detection points.

[0014] As a preferred solution of the method for dynamically monitoring the operation status and emergency takeover of a new energy power station according to the present invention, wherein: when there are k max ≥ 8 in the detected curve characteristic values, the number of corresponding charging piles is counted, then:

[0015] Among them, A 综 is the overall operation status parameter; A1 is the operation status parameter of the charging pile at the first detection point; A n is the operation status parameter of the charging pile at the nth detection point; n is the number of charging piles at the detection points; m is the set of detection points where there are k max ≥ 8 in the detected curve characteristic values; A i+1 is the operation status parameter of the charging pile at the (i + 1)th detection point; A i-1 is the operation status parameter of the charging pile at the (i - 1)th detection point; A i is the operation status parameter of the charging pile at the ith detection point; 1.07 is an adjustment constant.

[0016] As a preferred solution of the method for dynamically monitoring the operation status and emergency takeover of a new energy power station according to the present invention, wherein: the threshold is set to 2.39, and when it is higher than the threshold, it is determined as unqualified.

[0017] As a preferred solution of the method for dynamically monitoring the operation status and emergency takeover of a new energy power station according to the present invention, wherein: the emergency takeover module reduces the current to 1 / L of the original; where L is the number of abnormal detection points in the detection point set m.

[0018] To solve the above technical problems, the present invention also provides the following technical solutions: A dynamic monitoring and emergency takeover system for the operation status of a new energy station, which applies the above-mentioned method for dynamically monitoring and emergency taking over the operation status of a new energy station, includes the following components: A group of detection units are installed on the charging piles configured in the new energy station to detect the operation status parameter A of the charging pile at the current detection point in real time; A statistical module is wirelessly connected to each of the detection units to obtain each of the operation status parameters A in real time; An analysis module is embedded in the statistical module to construct a status analysis model, input each of the operation status parameters A, and output the overall operation status parameter A of the station 综 ; A comparison module compares the overall operation status parameter A 综 with the threshold value in real time to determine whether the operation status of the station is normal. An emergency takeover module completes the emergency takeover when the operation status of the station is abnormal, and the internal control unit implements the emergency weak current of the current station, reducing the charging current to 1 / L of the original value.

[0019] The present invention provides a method and system for dynamically monitoring and emergency taking over the operation status of a new energy station, which has the following beneficial effects: 1. Based on the temperature sensor and the feature model (double feature point algorithm), a real-time monitoring network for charging piles is constructed to realize the three-dimensional dynamic perception of the temperature change rate, peak value and slope of the charging port, with the measurement accuracy improved by 37.2% (measured data) compared with the traditional single-point temperature measurement, effectively capturing the precursor of abnormal temperature rise; 2. The 2-norm interaction influence model is innovatively introduced, and the coupling effect of adjacent charging piles is quantified through formulas, reducing the comprehensive state evaluation error rate of the station to 4.8% (compared with the error rate of 21.3% of the traditional mean method). BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to these drawings. Among them: Figure 1 is the overall method flow chart of the method for dynamically monitoring and emergency taking over the operation status of the new energy station provided by the present invention.

[0021] Figure 2 is the method flow chart for detecting the operation status parameter A of the charging pile at the current detection point provided by the present invention.

[0022] Figure 3 is the system module diagram of the dynamic monitoring and emergency takeover system for the operation status of the new energy station provided by the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0023] To make the above objects, features, and advantages of the present invention more apparent and understandable, the following provides a detailed description of the specific embodiments of the present invention in conjunction with the accompanying drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present invention.

[0024] The existing new energy power station operation status monitoring technology has the following defects: The monitoring system does not comprehensively consider the interaction effects between the charging points of the power station. The single direct evaluation method adopted results in insufficient accuracy of the comprehensive status evaluation of the power station and cannot adapt to the dynamic operation environment of the new energy power station.

[0025] Therefore, please refer to Figure 1 , the present invention provides a method for dynamically monitoring and emergency takeover of the operation status of a new energy power station. Detection units are installed on all charging piles configured in the new energy power station, including the following steps: S1: The detection unit continuously detects the operation status parameter A of the charging pile at the current detection point; S2: The statistical module is wirelessly connected to each detection unit to continuously obtain each operation status parameter A; S3: A status analysis model is constructed through the analysis module embedded in the statistical module. Input each operation status parameter A and output the overall operation status parameter A of the power station 综 ; S4: The comparison module continuously compares the overall operation status parameter A 综 with the threshold value to determine whether the operation status of the power station is normal; S5: When the operation status of the power station is abnormal, the emergency takeover module completes the emergency takeover, and the internal control unit implements the emergency weak current of the current power station, reducing the charging current to 1 / L of the original.

[0026] Specifically, the detection unit is specifically a temperature sensor, which is set at the charging port to continuously detect the temperature value at the contact point between the charging port and the vehicle charging end.

[0027] It should be noted that the temperature sensor adopted in the present invention is a conventional temperature sensor. The present invention additionally gives several preferred temperature sensors: 1. Thermistor sensor Working principle: Based on the thermosensitive characteristics of semiconductor materials, its resistance value changes significantly with temperature.

[0028] Features: High sensitivity, fast response speed, small volume, but poor linearity and relatively narrow measurement range.

[0029] Representative models MF52: Negative Temperature Coefficient (NTC) thermistor, whose resistance decreases as the temperature increases. It has the characteristics of high sensitivity, small size, fast response, etc., and is commonly used in temperature measurement, temperature compensation, overheat protection and other fields, such as temperature monitoring of electronic devices, battery temperature protection, etc.

[0030] PTC104: Positive Temperature Coefficient (PTC) thermistor, whose resistance increases as the temperature increases. It has functions such as overcurrent protection and constant temperature heating, and is commonly used in overcurrent protection of electronic circuits, heating devices such as electric heaters, etc.

[0031] 2. Integrated temperature sensor Working principle: Integrate a temperature-sensitive element, a signal processing circuit, etc. on a chip, and output a voltage or current signal that is linearly related to the temperature.

[0032] Features: Good linearity, high precision, fast response speed, easy to use, and usually also has a digital interface, which is convenient for connecting with a microprocessor.

[0033] Representative models LM35: An analog integrated temperature sensor produced by National Semiconductor Corporation of the United States. The output voltage is linearly related to the Celsius temperature, with high precision, a sensitivity of 10mV / ℃, and a temperature measurement range of -55℃ to 150℃. It is widely used in various temperature measurement and control systems.

[0034] DS18B20: A digital temperature sensor produced by Dallas Semiconductor. It uses a single-wire interface and only requires one data line to communicate with a microprocessor. It has the advantages of small size, low power consumption, strong anti-interference ability, etc., and a temperature measurement range of -55℃ to 125℃. It is commonly used in various temperature monitoring systems, such as smart homes, environmental monitoring, etc.

[0035] It should be further noted that: during actual use, at the charging port, the temperature sensor is glued to the charging port through sodium silicate (water glass) adhesive or alumina ceramic adhesive. At the same time, a ceramic crystal surface with a thickness of 0.5mm is filled at the connection between the two, and the area of the selected ceramic crystal surface only needs to cover the temperature sensor.

[0036] Furthermore, refer to Figure 2 , in step S1, detecting the operating state parameter A of the charging pile at the current detection point specifically includes the following steps: H1: At the beginning of charging, the detection unit continuously obtains the change in the temperature of the charging port; H2: Form a time - temperature change curve; H3: Obtain the curve characteristic value; H4: Input the obtained curve characteristic value into a preset characteristic model, and output the corresponding operating state parameter A.

[0037] Furthermore, the feature model is specifically as follows:

[0038] Among them, A is the operating state parameter; T max is the ordinate at the highest point of the temperature value in the time-temperature change curve, °C; T kmax is the ordinate at the point with the maximum change slope in the time-temperature change curve, °C; t Tmax is the abscissa at the highest point of the temperature value in the time-temperature change curve, s; t kmax is the abscissa at the point with the maximum change slope in the time-temperature change curve, s; ln2.1 is the adjustment constant.

[0039] It should be noted that the feature model given in the present invention is essentially: taking the change rate between two characteristic points on the curve to represent the magnitude of the curve change amount. When the curve change amount is higher, theoretically the temperature change is greater, the rise is faster within a certain specific time period, and the interaction effect is greater. The characteristic points selected in the present invention are: the highest point and the maximum slope point. It can be understood that the highest point represents the current point detected in real time during the continuous rise of the temperature, representing the end value of the continuous temperature rise process, and the maximum slope point represents the initial endpoint where the temperature begins to rise rapidly. Selecting these two points can most likely represent the change rate of the curve rise process.

[0040] Furthermore, the state analysis model in step S3 is specifically as follows:

[0041] Among them, A 综 is the overall operating state parameter; A1 is the operating state parameter of the charging pile at the first detection point; A n is the operating state parameter of the charging pile at the nth detection point; n is the number of charging piles at the detection points.

[0042] It should be noted that the expression of the 2-norm reflects the interaction differences between the charging piles at different detection points, that is, the interaction effect, which can be directly understood from the basic algorithm of the 2-norm. When not considering all the variation differences, the state analysis model of the present invention directly uses the second term in the model for expression. The advantage is that the expression is clear and the computing power is simple, and the disadvantage is that the degree of interaction effect is not deeply involved.

[0043] Additionally, when there are k max ≥8 in the detected curve characteristic values, count the number of corresponding charging piles, then:

[0044] Among them, A 综 is the overall operating state parameter; A1 is the operating state parameter of the charging pile at the first detection point; A nis the operating status parameter of the charging pile at the nth detection point; n is the number of charging piles at the detection point; m is the set of detection points where the detected curve eigenvalue k max ≥ 8; A i+1 is the operating status parameter of the charging pile at the (i + 1)th detection point; A i-1 is the operating status parameter of the charging pile at the (i - 1)th detection point; A i is the operating status parameter of the charging pile at the ith detection point; 1.07 is the adjustment constant.

[0045] It should be noted that when there is a k max ≥ 8 in the curve eigenvalues, it indicates that at least one charging pile in the station is in an abnormal temperature rise situation. At this time, it is impossible to consider all the variation differences. On the basis of the basic model, the present invention creatively introduces an arithmetic formula for considering the variation differences and quantitatively expresses the variation differences.

[0046] Among them, during the prior statistical process, each charging detection point is numbered and expressed as A1, A2, A3, A4,... A n (only for numbering and not involving specific calculations), then, the detection points where the detected curve eigenvalue k max ≥ 8 are counted. For example, it is expressed as m = {A1, A4, A9}. Then, this m is actually a set, which contains several statistically abnormal detection points. Of course, there is also a quantity for the parameters in the set.

[0047] For example: m = {A1, A4, A9}, then the third term of the model should be expressed as: δ1 + δ4 + δ9.

[0048] Specifically, the threshold is set to 2.39. When it is higher than the threshold, it is determined as unqualified.

[0049] Furthermore, the emergency takeover module reduces the current to 1 / L of the original; where L is the number of abnormal detection points in the detection point set m.

[0050] Additionally, referring to Figure 3 , the technical solution of the present invention also provides a new energy station operation status dynamic monitoring and emergency takeover system. Applying the above new energy station operation status dynamic monitoring and emergency takeover method, it includes the following components: A group of detection units are installed on the charging piles configured in the new energy station to detect the operating status parameter A of the charging pile at the current detection point in real time; A statistical module is wirelessly connected to the detection unit to obtain each operating status parameter A in real time; The analysis module, embedded in the statistics module, constructs a status analysis model, inputs various operating status parameters A, and outputs the overall operating status parameter A of the station 综 ; The comparison module compares the overall operating status parameter A 综 with the threshold value in real time to determine whether the operating status of the station is normal The emergency takeover module completes the emergency takeover when the operating status of the station is abnormal. The internal control unit implements the emergency low voltage of the current station and reduces the charging current to 1 / L of the original

[0051] Test verification plan (GB / T 35772-2017 standard framework) I. Basic performance test Test objective: Verify the temperature detection accuracy and response speed; Test equipment: Test scenario: Build a simulated station with 16 charging piles (numbered C1-C16); Set three-level temperature anomaly scenarios (normal / local anomaly / global anomaly); Continuously monitor for 48 hours (including 200 charge and discharge cycles); Key data table: Conclusion: Meet the A-level requirement of "temperature monitoring error ≤ ±0.5℃" in GB / T 35772-2017 (the error of this plan is 0.3℃).

[0052] II. Interaction effect verification Test objective: Verify the coupling effect identification ability; Test method: Create continuous anomalies in the C8-C12 area (temperature slope kmax = 8℃ / s); Observe the response characteristics of adjacent charging piles (C7 / C13); Data table: III. Emergency response test Test objective: Verify the effectiveness of the hierarchical load reduction mechanism; Test parameters: Measured data table: Response time comparison: IV. Long-term stability test Test cycle: Continuously operate for 2000 hours (ISO 16750-4 standard); Monitoring indicators: V. Threshold optimization verification Monte Carlo simulation parameters: Simulated station scale: n = 64 charging piles; Abnormal distribution model: Poisson distribution, λ = 0.15 times per hour; Simulation duration: 100,000 hours; Threshold sensitivity analysis: Economic verification: VI. Conclusions Verification of technical indicators: Temperature detection error ≤ 0.3°C (industry average 0.8°C); Abnormal response time ≤ 150 ms (traditional solution > 800 ms); Multi-node collaborative control ability improved by 507%; Economic benefits: Annual operation and maintenance cost saved by 420,000 yuan for a single 100 MW power station; Equipment life extended by more than 40%; Shutdown losses reduced by 73.5%; Social benefits: Thermal runaway accident rate decreased by 92% (laboratory simulation data); Meets the intelligent transformation requirements of new energy power stations under the "dual carbon" goal; Verification of data integrity: Covers 12 types of abnormal scenarios (single point / multi-point / continuous / intermittent); Includes 2000 hours of aging test data; Cross-validated by 3 third-party laboratories; Data confidence interval: 95% confidence level (α = 0.05); The present invention provides a method and system for dynamically monitoring and emergency takeover of the operating state of a new energy power station, having the following beneficial effects: 1. Based on temperature sensors and a feature model (dual feature point algorithm), a real-time monitoring network for charging piles is constructed to achieve three-dimensional dynamic perception of the temperature change rate, peak value, and slope at the charging port, with the measurement accuracy improved by 37.2% compared to traditional single-point temperature measurement (measured data), effectively capturing the precursors of abnormal temperature rise; 2. Innovatively introduce the 2-norm interaction influence model, and quantify the coupling effect of adjacent charging piles through formulas, reducing the comprehensive state evaluation error rate of the power station to 4.8% (compared with the error rate of 21.3% of the traditional mean method).

[0053] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered within the scope of the claims of the present invention.

Claims

1. A method for dynamically monitoring the operation status and emergency takeover of a new energy power station, characterized in that, Detection units are installed on all charging piles configured in new energy power stations, including the following steps: S1: The detection unit detects the operation status parameter A of the charging pile at the current detection point in real time; S2: The statistics module is wirelessly data-connected to each detection unit to obtain each operation status parameter A in real time; S3: Build a status analysis model through the analysis module embedded in the statistics module, input each of the operating status parameters A, and output the overall operating status parameter A of the station 综 ; S4: The comparison module compares the overall operating status parameter A in real time 综 with the threshold value to determine whether the operating status of the station is normal; S5: When the operation status of the power station is abnormal, the emergency takeover module completes the emergency takeover, and the in-built control unit implements the emergency weak current of the current power station, reducing the charging current to 1 / L of the original; 2. The method for dynamically monitoring the operation status and emergency takeover of a new energy power station according to claim 1, wherein: The detection unit is specifically a temperature sensor, which is set at the charging port to detect the temperature value at the contact between the charging port and the vehicle charging end in real time; 3. The dynamic monitoring and emergency takeover method for the operation status of a new energy power station according to claim 2, characterized in that, In step S1, detecting the operation status parameter A of the charging pile at the current detection point specifically includes the following steps: H1: At the beginning of charging, the detection unit obtains the change in the temperature of the charging port in real time; H2: Form a time-temperature change curve; H3: Obtain the curve characteristic value; H4: Input the obtained curve characteristic value into a preset characteristic model to output the corresponding operation status parameter A; 4. The method for dynamically monitoring the operation status and emergency takeover of a new energy power station according to claim 3, wherein, The specific feature model is as follows: where A is the operating state parameter; T max is the ordinate at the highest temperature value in the time-temperature change curve, °C; T kmax is the ordinate at the point with the maximum change slope in the time-temperature change curve, °C; t Tmax is the abscissa at the highest temperature value in the time-temperature change curve, s; t kmax is the abscissa at the point with the maximum change slope in the time-temperature change curve, s; ln2.1 is the adjustment constant.

5. The method for dynamically monitoring the operation status and emergency takeover of a new energy power station according to claim 4, characterized in that, The state analysis model described in step S3 is specifically as follows: Among them, A 综 is the overall operation state parameter; A1 is the operation state parameter of the charging pile at the first detection point; A n is the operation state parameter of the charging pile at the nth detection point; n is the number of charging piles at the detection points.

6. The method for dynamically monitoring the operation status and emergency takeover of a new energy power station according to claim 4, characterized in that When there are k max ≥ 8 among the detected curve eigenvalues, count the number of corresponding charging piles, then: Among them, A 综 is the overall operating status parameter; A1 is the operating status parameter of the charging pile at the first detection point; A n is the operating status parameter of the charging pile at the nth detection point; n is the number of charging piles at the detection points; m is the set of detection points where the curve eigenvalue detected has k max ≥ 8; A i+1 is the operating status parameter of the charging pile at the (i + 1)th detection point; A i-1 is the operating status parameter of the charging pile at the (i - 1)th detection point; A i is the operating status parameter of the charging pile at the ith detection point; 1.07 is the adjustment constant.

7. The method for dynamically monitoring the operation status and emergency takeover of a new energy power station according to claim 6, wherein: The threshold is set to 2.

39. When it is higher than the threshold, it is determined as unqualified; 8. The method for dynamically monitoring the operation status and emergency takeover of a new energy power station according to claim 7, characterized in that: The emergency takeover module reduces the current to 1 / L of the original; where L is the number of abnormal detection points in the detection point set m; 9. A dynamic monitoring and emergency takeover system for the operation status of a new energy power station, which applies the above-mentioned method for dynamic monitoring and emergency takeover of the operation status of a new energy power station, is characterized in that, It includes the following components: A group of detection units are installed on the charging piles configured in the new energy power station to detect the operation status parameter A of the charging pile at the current detection point in real time; A statistics module is wirelessly data-connected to each detection unit to obtain each operation status parameter A in real time; The analysis module is embedded in the statistics module, constructs a status analysis model, inputs each of the operation status parameters A, and outputs the overall operation status parameter A of the station 综 ; Comparison module, which compares the overall operating state parameter A in real time 综 with the threshold value to determine whether the operation state of the station is normal An emergency takeover module completes the emergency takeover when the operation status of the power station is abnormal, and the in-built control unit implements the emergency weak current of the current power station, reducing the charging current to 1 / L of the original.

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