A 5G private network monitoring method and system for new energy equipment

Abstract

The present invention discloses a 5G private network monitoring method and system for new energy equipment, which belongs to the field of new energy equipment power generation supervision, and solves the problem of how to integrate and utilize data obtained by communication transmission to accurately monitor and evaluate whether a single new energy equipment has an abnormality, so that relevant staff can deal with it in time, and then deal with the new energy power generation problem from the source, and achieve better management of new energy power generation; including: analyzing and obtaining whether the operation of the target new energy equipment in the past preset time period is stable and whether the communication is stable, and evaluating the current operating risk level of the target new energy equipment; obtaining electrical parameter data to analyze and obtain the electrical abnormality level of the target new energy equipment in the past preset time period; if the target new energy equipment is marked as having a high risk in its current operating state, a comprehensive analysis is conducted to determine whether a fault warning is required for the operation of the current target new energy equipment.

Description

Technical Field

[0001] The present invention belongs to the field of power generation supervision of new energy equipment, and specifically provides a 5G private network monitoring method and system for new energy equipment. Background Art

[0002] Renewable energy generation technology has developed rapidly in recent decades and has become an important means to replace traditional fossil energy. Renewable energy generation technology mainly includes wind energy, solar energy, biomass energy, geothermal energy and ocean energy, which have the advantages of being clean, renewable and low-carbon. At present, in order to ensure the stable and sustainable operation of renewable energy generation, 5G private network technology can be used to remotely transmit and monitor new energy equipment.

[0003] However, both large-scale centralized photovoltaic power stations and distributed photovoltaic power stations contain a large number of new energy equipment, and the operation of new energy equipment generates a lot of data. How to integrate and use the data obtained by communication transmission to accurately monitor and evaluate whether a single new energy equipment has abnormalities, so that relevant staff can handle them in time, and then deal with new energy power generation problems from the source, and achieve better management of new energy power generation, is an urgent problem to be solved. To this end, the present invention proposes a 5G private network monitoring method and system for new energy equipment. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art. To this end, the present invention proposes a 5G private network monitoring method and system for new energy equipment, which solves the problem of how to integrate and utilize data obtained through communication transmission to accurately monitor and evaluate whether a single new energy device has an abnormality, so that relevant staff can handle it in a timely manner, thereby handling the new energy power generation problem from the source and achieving better management of new energy power generation.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] A 5G private network monitoring method for new energy equipment, comprising:

[0007] Step S1: Analyze and obtain whether the operation and communication of the target new energy equipment are stable in the past preset time period, and evaluate the current operation risk hidden danger degree of the target new energy equipment based on whether the operation and communication of the target new energy equipment are stable in the past preset time period;

[0008] Step S2: obtaining electrical parameter data of the target new energy equipment in the past preset time period, and obtaining the degree of electrical abnormality of the target new energy equipment in the past preset time period based on the electrical parameter data analysis;

[0009] Step S3: If the target new energy equipment is marked as having a high risk in its current operating state, an analysis is performed based on whether the target new energy equipment has been operating stably, whether its communication is stable, and the degree of electrical abnormality in the past preset time period to determine whether a fault warning is needed for the current operation of the target new energy equipment.

[0010] Further, in step S1, the method of analyzing and obtaining whether the operation of the target new energy equipment in the past preset time period is stable includes:

[0011] Obtaining the startup records and start-stop records of the target new energy equipment in the past preset time period; based on the acquired startup records and start-stop records of the target new energy equipment in the past preset time period, obtaining the total startup times and total start-stop times of the target new energy equipment in the past preset time period;

[0012] The ratio of the total number of starts of the target new energy equipment in the past preset time period to the preset time period is marked as the start frequency PD, and the ratio of the total number of starts and stops of the target new energy equipment in the past time period to the preset time period is marked as the start-stop frequency PT;

[0013] Based on the starting frequency PD and the start-stop frequency PT of the target new energy equipment in the past preset time period, the operation stability index QK of the target new energy equipment in the past preset time period is calculated, and the formula is as follows:

[0014]

[0015] Wherein, PDmax and PTmax are the maximum starting frequency and maximum start-stop frequency of the target new energy equipment within the preset time period, a1 and a2 are the weight coefficients of the starting frequency ratio and the start-stop frequency ratio, and the values ​​of a1 and a2 are both greater than 0; γ represents the correction coefficient;

[0016] Compare the calculated operation stability index of the target new energy equipment in the past preset time period with the preset operation stability index threshold to determine whether the operation of the target new energy equipment in the past preset time period is stable;

[0017] If the operation stability index of the target new energy equipment in the past preset time period is greater than the preset operation stability index threshold, an operation stability signal is generated;

[0018] If the operation stability index of the target new energy equipment in the past preset time period is less than or equal to the preset operation stability index threshold, an operation instability signal is generated.

[0019] Further, in step S1, the method of analyzing and obtaining whether the communication of the target new energy device is stable within the past preset time period includes:

[0020] According to the type of the past preset time period, the past preset time period is divided into a number of time intervals Δti; i represents the number of the time interval, i=1,2...n; n represents the total number of time intervals included in the preset time period of the corresponding type;

[0021] Count the number of network disconnections Ci in each time interval Δti, and calculate the average number of network disconnections ΔC in each time interval Δti. The formula is:

[0022] According to the number of network disconnections Ci in each time interval Δti and the average number of network disconnections ΔC in each time interval Δti, the communication stability index ZQ of the target new energy equipment in the past preset time period is calculated, and the formula is:

[0023] In the formula, fi represents the weight coefficient of the time zone numbered i, and fi is greater than 0;

[0024] Compare the communication stability index of the target new energy device obtained by calculation in the past preset time period with the preset communication stability index threshold to determine the communication stability of the target new energy device in the past preset time period;

[0025] If the communication stability index of the target new energy device in the past preset time period is greater than the preset communication stability index threshold, a communication stability signal is generated;

[0026] If the communication stability index of the target new energy equipment in the past preset time period is less than or equal to a preset communication stability index threshold, a communication instability signal is generated.

[0027] Furthermore, the types of preset time periods include: one day, one week, one month, one quarter and one year; different types of preset periods all use the logic of peak power consumption, low power consumption and level segment to divide the time interval.

[0028] Further, in step S1, the current operation risk level of the target new energy equipment is evaluated based on whether the operation and communication of the target new energy equipment are stable in the past preset time period, including:

[0029] If the target new energy equipment has unstable operation or unstable communication in the past preset time period, the current operation state of the target new energy equipment is marked as having a high risk;

[0030] If the target new energy device has been operating stably and communicating stably in the past preset time period, the target new energy device is marked as having low risk in its current operating state.

[0031] Further, in step S2, electrical parameter data of the target new energy device in the past preset time period is obtained, and the degree of electrical abnormality of the target new energy device in the past preset time period is obtained based on the electrical parameter data analysis; including:

[0032] Acquire electrical parameter data of the target new energy equipment within a preset time period in the past, and classify the acquired electrical parameter data into m electrical parameter data sets according to the type of the electrical parameters;

[0033] Compare the electrical parameter values ​​contained in each acquired electrical parameter data set with the preset standard range of the corresponding type of electrical parameters, and count the number of time intervals N1j in which the electrical parameters of the jth type of the target new energy equipment do not meet the preset standard range in the past preset time period; count the number of types N2i of electrical parameters of the target new energy equipment that do not meet the corresponding preset standard range in the i-th time interval in the past preset time period; and count the total number N4i of electrical parameter values ​​of the target new energy equipment in the past preset time period and the number N3i,j of electrical parameter values ​​of the jth type of electrical parameters in the i-th time interval that do not meet the corresponding preset standard range; wherein j=1,2…m; m represents the total number of types of electrical parameters contained in the target new energy equipment;

[0034] Calculate the electrical abnormality index YD of the target new energy equipment in the past preset time period, the formula is:

[0035]

[0036] Wherein, g1 and g2 are both preset weight coefficients greater than 0.

[0037] Further, in step S3, if the target new energy equipment is marked as having a high risk in its current operating state, an analysis is performed based on whether the target new energy equipment is operating stably, whether the communication is stable, and the degree of electrical abnormality in the past preset time period to determine whether a fault warning is required for the operation of the current target new energy equipment; including:

[0038] Obtain the operation stability index QK, communication stability index ZQ and electrical abnormality index YD of the target new energy equipment in the past preset time period; calculate the current operation abnormality trend index KS of the target new energy equipment; the formula is:

[0039] Wherein, k1, k2 and k3 are the preset weight coefficients of the operation stability index QK, the communication stability index ZQ and the electrical abnormality index YD respectively; the values ​​of k1, k2 and k3 are all greater than 0;

[0040] Compare the calculated current abnormal operation trend index of the target new energy equipment with the corresponding preset abnormal operation trend index threshold to determine whether a fault warning is required for the operation of the current target new energy equipment;

[0041] If the current abnormal operation trend index of the target new energy equipment is greater than or equal to the corresponding preset abnormal operation trend index threshold, a signal of operation failure warning is generated;

[0042] If the current abnormal operation trend index of the target new energy equipment is less than the corresponding preset abnormal operation trend index threshold, a normal operation signal is generated;

[0043] When a signal of a fault warning of the target new energy equipment is generated, the unique identifier, geographic location information and fault warning signal of the target new energy equipment are sent to the corresponding technician user terminal to notify the corresponding technician to handle it in time.

[0044] Further, a 5G private network monitoring system for new energy equipment is used to implement a 5G private network monitoring method for new energy equipment, including: an operation stability analysis module, a communication stability analysis module, a risk pre-assessment module, an electrical anomaly analysis module and an intelligent decision-making module;

[0045] The operation stability analysis module is used to analyze whether the operation of the target new energy equipment has been stable in the past preset time period;

[0046] The communication stability analysis module is used to analyze whether the communication of the target new energy equipment is stable within the past preset time period;

[0047] The risk pre-assessment module is used to assess the current operation risk potential of the target new energy equipment based on whether the operation of the target new energy equipment is stable and whether the communication is stable in the past preset time period;

[0048] The electrical anomaly analysis module is used to obtain electrical parameter data of the target new energy equipment in the past preset time period, and obtain the degree of electrical anomaly of the target new energy equipment in the past preset time period based on the electrical parameter data analysis;

[0049] The intelligent decision-making module is used to determine whether a fault warning is needed for the operation of the current target new energy equipment when the target new energy equipment is marked as a risk in its current operating status, based on whether the operation of the target new energy equipment has been stable, whether the communication is stable, and the degree of electrical abnormality in the past preset time period.

[0050] Compared with the prior art, the present invention has the following beneficial effects:

[0051] 1. In the present invention, by utilizing the startup record and start-stop record of the target new energy equipment in the past preset time period, the operation stability index of the target new energy equipment in the past preset time period is calculated, and whether the operation of the target new energy equipment in the past preset time period is analyzed based on the operation stability index, it can directly reveal the potential mechanical, electrical and thermal stress problems of the new energy equipment and reflect the potential instability of the equipment; and by analyzing and statistically analyzing the communication drop performance data of the new energy equipment in several time intervals in the past preset time period to calculate the communication stability index of the target new energy equipment in the past preset time period, based on the communication stability index, whether the communication of the target new energy equipment in the past preset time period is stable, it can reflect the communication connection between the new energy equipment and the network from the side, if there is unstable communication, it will cause abnormal detection omission or delay; and combine whether the operation is stable and whether the communication is stable to evaluate the current operation risk hidden danger degree of the new energy equipment, so as to provide a prerequisite for the subsequent judgment of the current abnormal operation trend of the new energy equipment.

[0052] 2. In the present invention, the electrical anomaly degree index of the target new energy equipment in the past preset time period is calculated by analyzing the electrical parameter data of the target new energy equipment in the past preset time period, so as to analyze whether the electrical of the new energy equipment is abnormal from the probability perspective of the electrical parameters, and provide supplementary conditions for the subsequent judgment of the abnormal operation trend of the new energy equipment in the current period.

[0053] 3. By judging whether the current operating status of the target new energy equipment poses a high risk, if so, the target new energy equipment is analyzed for stability in operation, stability in communication, and the degree of electrical abnormality within the past preset time period to determine whether a fault warning is needed for the current target new energy equipment. Further analysis and judgment can be made based on the direct judgment of the degree of risk, so that it can be more accurately and reliably analyzed to determine whether the corresponding new energy equipment has abnormal failures, thereby preventing single-minded misjudgment in the early stage. Through multi-angle monitoring and evaluation, it helps to improve the safety, reliability, and stability of new energy equipment and power station operations, reduce the negative impact of potential failures of new energy equipment on power station power generation operations, and provide timely fault warning prompts for later equipment operation and maintenance, thereby addressing new energy power generation issues at the source and achieving better management of new energy power generation. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 A schematic diagram of a 5G private network monitoring method for new energy equipment according to the present invention;

[0055] Figure 2 This is a structural schematic diagram of a 5G private network monitoring system for new energy equipment according to the present invention. DETAILED DESCRIPTION

[0056] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0057] Example 1

[0058] like Figure 1 As shown, a 5G private network monitoring method for new energy equipment includes the following steps:

[0059] Step S1: Analyze and obtain whether the operation and communication of the target new energy equipment are stable in the past preset time period, and evaluate the current operation risk hidden danger degree of the target new energy equipment based on whether the operation and communication of the target new energy equipment are stable in the past preset time period;

[0060] Step S2: obtaining electrical parameter data of the target new energy equipment in the past preset time period, and obtaining the degree of electrical abnormality of the target new energy equipment in the past preset time period based on the electrical parameter data analysis;

[0061] Step S3: If the target new energy equipment is marked as having a high risk in its current operating state, an analysis is performed based on whether the target new energy equipment has been operating stably, whether its communication is stable, and the degree of electrical abnormality in the past preset time period to determine whether a fault warning is required for the current operation of the target new energy equipment;

[0062] The new energy equipment in this embodiment is applied to photovoltaic power plants. The whole process of photovoltaic power generation is equipped with various types of new energy equipment, including: photovoltaic modules, inverters, junction boxes, energy storage systems, environmental detection devices, etc.; whether it is a large-scale centralized photovoltaic power station or a distributed photovoltaic power station, it contains a large number of new energy equipment. It is not easy to find a single new energy equipment failure. In order to monitor and warn the abnormality of new energy equipment in real time, a 5G private network can be used to transmit the data generated by each new energy equipment; and based on the data obtained by the 5G private network transmission, the new energy equipment operation is monitored and warned, so as to monitor whether the photovoltaic power generation is abnormal and achieve stable power generation;

[0063] Optionally, in step S1, the method of analyzing and obtaining whether the operation of the target new energy equipment in the past preset time period is stable includes:

[0064] Obtaining the startup records and start-stop records of the target new energy equipment in the past preset time period; based on the acquired startup records and start-stop records of the target new energy equipment in the past preset time period, obtaining the total startup times and total start-stop times of the target new energy equipment in the past preset time period;

[0065] It should be noted that, in this embodiment, the new energy equipment of the power station is periodically supervised, and multiple period types are set to achieve accurate monitoring and maintenance of the new energy equipment of the corresponding power station, thereby achieving sustainable and stable power generation; specifically, the types of preset time periods include: one day, one week, one month, one quarter, one year, etc.;

[0066] The ratio of the total number of starts of the target new energy equipment in the past preset time period to the preset time period is marked as the start frequency PD, and the ratio of the total number of starts and stops of the target new energy equipment in the past time period to the preset time period is marked as the start-stop frequency PT;

[0067] Based on the starting frequency PD and the start-stop frequency PT of the target new energy equipment in the past preset time period, the operation stability index QK of the target new energy equipment in the past preset time period is calculated, and the formula is as follows:

[0068]

[0069] Wherein, PDmax and PTmax are the maximum starting frequency and maximum start-stop frequency of the target new energy equipment within the preset time period, a1 and a2 are the weight coefficients of the starting frequency ratio and the start-stop frequency ratio, and the values ​​of a1 and a2 are both greater than 0; γ represents the correction coefficient;

[0070] Understandably, It indicates the ratio of the starting frequency to the maximum starting frequency allowed by the design. The larger the value, the lower the starting frequency, which is more beneficial to stability. Multiplying it by the weight coefficient a1 indicates the influence of the starting frequency on the stable operation of new energy equipment. It indicates the ratio of the start-stop frequency to the maximum start-stop frequency allowed by the design. The larger the value, the lower the start-stop frequency, which is more beneficial to stability. Multiplying it by the weight coefficient a2 indicates the influence of the start-stop frequency on the stable operation of new energy equipment. Represents the relationship between the start-stop frequency domain and the start frequency through an exponential function indicates the negative impact of this relationship on operational stability;

[0071] It is understandable that the operation stability index directly reflects the operation behavior of new energy equipment and can reveal potential mechanical, electrical and thermal stress problems. Changes in the operation stability index can often directly determine equipment performance degradation and unreasonable operation;

[0072] Compare the calculated operation stability index of the target new energy equipment in the past preset time period with the preset operation stability index threshold to determine whether the operation of the target new energy equipment in the past preset time period is stable; wherein the preset operation stability index threshold is obtained by analyzing a large number of operation stability index calculations and abnormal situations of actual start-up and stop of the new energy equipment in the early stage;

[0073] If the operation stability index of the target new energy equipment in the past preset time period is greater than the preset operation stability index threshold, an operation stability signal is generated;

[0074] If the operation stability index of the target new energy equipment in the past preset time period is less than or equal to the preset operation stability index threshold, an operation instability signal is generated;

[0075] Optionally, in step S1, the method of analyzing and obtaining whether the communication of the target new energy device is stable within the past preset time period includes:

[0076] According to the type of the past preset time period, the past preset time period is divided into a number of time intervals Δti; i represents the number of the time interval, i=1,2...n; n represents the total number of time intervals contained in the preset time period of the corresponding type; wherein different types of preset periods all use the logic of peak power consumption, low power consumption, and level power segment to divide the time intervals. It can be understood that the time period at the peak power consumption is divided into one time interval, the time period at the low power consumption is divided into one time interval, and the time period at the level power segment is divided into one time interval; within the same time period, the time intervals are arranged in chronological order;

[0077] Count the number of network disconnections Ci in each time interval Δti, and calculate the average number of network disconnections ΔC in each time interval Δti. The formula is:

[0078] According to the number of network disconnections Ci in each time interval Δti and the average number of network disconnections ΔC in each time interval Δti, the communication stability index ZQ of the target new energy equipment in the past preset time period is calculated, and the formula is:

[0079] In the formula, fi represents the weight coefficient of the time zone numbered i, and fi is greater than 0;

[0080] It can be understood that the types of preset time periods include one day, one week, one month, one quarter, one year, etc.; different types of preset time periods are set with different time intervals. For example, when the type of preset time period is one day, it is necessary to consider the power consumption of users at different time points, and the amount of power consumption will directly affect the power output of the power station, and then affect the operating load of each new energy equipment used in the power station. In this embodiment, the weight coefficients of each time zone corresponding to different types of preset time periods are not the same. In the early stage, the weight coefficients of different time intervals can be set by technicians in this field according to the usual communication performance of the 5G private network of the power station's new energy equipment;

[0081] It can be understood that the larger the value of the communication stability index, the more stable the number of network disconnections, and the smaller the value, the greater the fluctuation and instability of the network disconnections; wherein, the square of the standardized deviation of the number of network disconnections in each time interval from the average value reflects the dispersion of the number of network disconnections in each time interval, which can be used to measure the stability of communication and reflect the degree of fluctuation of network disconnections within the entire preset time period;

[0082] The communication stability index of the target new energy device obtained by calculation in the past preset time period is compared with the preset communication stability index threshold to determine the communication stability of the target new energy device in the past preset time period; wherein the preset communication stability index threshold is obtained by technicians in this field in the early stage based on the actual communication situation of the new energy device using 5G private network communication;

[0083] If the communication stability index of the target new energy device in the past preset time period is greater than the preset communication stability index threshold, a communication stability signal is generated;

[0084] If the communication stability index of the target new energy device in the past preset time period is less than or equal to the preset communication stability index threshold, a communication instability signal is generated;

[0085] It should be noted that the stability of communication is directly related to the monitoring and control of new energy equipment, affecting the effectiveness and timeliness of the operation and maintenance management of new energy equipment in the later stage. Poor communication quality will lead to omissions and delays in monitoring, affecting the rapid response to faults.

[0086] Optionally, in step S1, the current operation risk level of the target new energy equipment is evaluated based on whether the operation and communication of the target new energy equipment are stable in the past preset time period, including:

[0087] If the target new energy equipment has unstable operation or unstable communication in the past preset time period, the current operation state of the target new energy equipment will be marked as having a high risk of hidden danger; at this time, it is necessary to analyze and determine whether a fault warning is needed in combination with the electrical parameter data of the target new energy equipment in the past preset time period;

[0088] If the target new energy equipment has been operating stably and communicating stably in the past preset time period, the target new energy equipment is marked as having a low risk in its current operating state; no fault warning is issued at this time;

[0089] In the present invention, by using the startup record and start-stop record of the target new energy device in the past preset time period, the operation stability index of the target new energy device in the past preset time period is calculated, and based on the operation stability index, whether the operation of the target new energy device in the past preset time period is analyzed to be stable, which can directly reveal the potential mechanical, electrical and thermal stress problems of the new energy device and reflect the potential instability of the device; and by analyzing the statistical communication drop performance data of the new energy device in several time intervals in the past preset time period, the communication stability index of the target new energy device in the past preset time period is calculated, and based on the communication stability index, whether the communication of the target new energy device in the past preset time period is analyzed to be stable, which can reflect the communication connection between the new energy device and the network from the side. If there is unstable communication, it will cause abnormal detection omission or delay; and the current operation risk hidden danger degree of the new energy device is evaluated in combination with whether the operation is stable and whether the communication is stable, so as to provide a prerequisite for the subsequent judgment of the current abnormal operation trend of the new energy device;

[0090] Optionally, in step S2, electrical parameter data of the target new energy device in the past preset time period is obtained, and the degree of electrical abnormality of the target new energy device in the past preset time period is obtained based on the electrical parameter data analysis; including:

[0091] The electrical parameter data of the target new energy equipment in the past preset time period are obtained, and the obtained electrical parameter data are classified into m electrical parameter data sets according to the types of electrical parameters; wherein the electrical parameters refer to various parameters related to the electrical performance and operating status of the new energy equipment, and common electrical parameters include voltage, current, power, power factor, etc.; there are differences in the electrical parameters contained in different new energy equipment; the electrical parameter data set contains the electrical parameter values ​​of the corresponding type of electrical parameters detected and obtained at different time points; wherein m represents the total number of types of electrical parameters contained in the target new energy equipment;

[0092] The electrical parameter values ​​contained in each acquired electrical parameter data set are compared with the preset standard range of the corresponding type of electrical parameters, and the number of time intervals N1j in which the electrical parameters of the jth type of the target new energy equipment do not meet the preset standard range in the past preset time period is counted. This statistical indicator can reflect the abnormal frequency of each type of electrical parameter in the entire preset time period; the number of types of electrical parameters that do not meet the corresponding preset standard range in the i-th time interval of the target new energy equipment in the past preset time period is counted N2i, and this statistical indicator can reflect the number of electrical parameter types that have abnormalities in each time interval, reflecting the extensiveness of the abnormality; and the total number of electrical parameter values ​​N4i of the target new energy equipment in the past preset time period and the number of electrical parameter values ​​N3i,j of the jth type of electrical parameters that do not meet the corresponding preset standard range in the i-th time interval are counted. This statistical indicator is refined to the specific number of abnormal values, reflecting the specific situation of the abnormality; wherein, i=1,2…n; n represents the total number of time intervals contained in the preset time period of the corresponding type; j=1,2…m; m represents the total number of types of electrical parameters contained in the target new energy equipment;

[0093] Calculate the electrical abnormality index YD of the target new energy equipment in the past preset time period, the formula is:

[0094]

[0095] In the formula, g1 and g2 are both preset weight coefficients greater than 0, and the values ​​of g1 and g2 are obtained by technicians in the previous stage based on the performance analysis of electrical parameters of the target new energy equipment under normal operation and abnormal operation;

[0096] Understandably, Indicates the average value of the number of time intervals in which each electrical parameter of the target new energy equipment does not meet the corresponding preset standard range in the past preset time period; Indicates the average value of the number of types of electrical parameters of the target new energy equipment that do not meet the corresponding preset standard range in each time interval within the past preset time period; It indicates the average value of the number of electrical parameter values ​​of each type of electrical parameter of the target new energy equipment that do not meet the corresponding preset standard range in each time interval during the past preset time period; The smaller the value, The smaller the value, The smaller it is, the smaller the degree of electrical abnormality of the target new energy equipment in the past preset time period is; by comprehensively considering the long-term abnormal frequency, the extensiveness of abnormalities in the time interval and the specific number of abnormalities, it reflects the electrical abnormalities of new energy equipment from multiple angles and provides effective statistical indicators for the evaluation of equipment operation status and fault diagnosis;

[0097] In the present invention, the electrical anomaly index of the target new energy device in the past preset time period is calculated by analyzing the electrical parameter data of the target new energy device in the past preset time period, so as to analyze whether the electrical of the new energy device is abnormal from the probability perspective of the electrical parameters, and provide supplementary conditions for the subsequent judgment of the current abnormal operation trend of the new energy device;

[0098] Optionally, in step S3, if the target new energy equipment is marked as having a high risk in its current operating state, an analysis is performed based on whether the target new energy equipment has been operating stably, whether the communication is stable, and the degree of electrical abnormality in the past preset time period to determine whether a fault warning is required for the operation of the current target new energy equipment; including:

[0099] Obtain the operation stability index QK, communication stability index ZQ and electrical abnormality index YD of the target new energy equipment in the past preset time period;

[0100] Based on the acquired operation stability index QK, communication stability index ZQ and electrical abnormality index YD of the target new energy equipment in the past preset time period, the current operation abnormality trend index KS of the target new energy equipment is calculated; the formula is:

[0101]

[0102] Wherein, k1, k2 and k3 are the preset weight coefficients of the operation stability index QK, the communication stability index ZQ and the electrical abnormality index YD respectively; the values ​​of k1, k2 and k3 are all greater than 0;

[0103] It can be understood that the larger the value of the abnormal operation trend KS is, the greater the risk of failure of the target new energy equipment in the current operation, and the failure warning needs to be carried out in advance;

[0104] Compare the calculated current abnormal operation trend index of the target new energy equipment with the corresponding preset abnormal operation trend index threshold to determine whether a fault warning is required for the operation of the current target new energy equipment;

[0105] If the current abnormal operation trend index of the target new energy equipment is greater than or equal to the corresponding preset abnormal operation trend index threshold, a signal of operation failure warning is generated;

[0106] If the current abnormal operation trend index of the target new energy equipment is less than the corresponding preset abnormal operation trend index threshold, a normal operation signal is generated;

[0107] When a signal of a fault warning of the target new energy equipment is generated, the unique identifier, geographic location information and fault warning signal of the target new energy equipment are sent to the corresponding technician user terminal to notify the corresponding technician to handle it in time;

[0108] Among them, the values ​​of k1, k2, k3 and the preset operation abnormality trend index threshold are obtained by those skilled in the art through a large amount of data calculation of the operation stability index, communication stability index, electrical abnormality index and operation abnormality trend index of the target new energy equipment in the early stage, and combined with the actual fault abnormal performance analysis of the target new energy equipment in the corresponding preset time period;

[0109] By judging whether the target new energy equipment has a high risk of hidden danger in its current operation state, if it has a high risk of hidden danger, combining the operation stability of the target new energy equipment in the past preset time period, the stability of the communication and the degree of electrical abnormality, it is judged whether it is necessary to issue a fault warning for the operation of the current target new energy equipment. Under the premise of directly judging the degree of hidden danger, further analysis and judgment can be made, so as to more accurately and reliably analyze whether the corresponding new energy equipment has abnormal faults, and prevent single judgment errors in the early stage. Through multi-angle monitoring and evaluation, it is helpful to improve the safety, reliability and stability of the operation of new energy equipment and power station, reduce the negative impact of potential failures of new energy equipment on the power generation operation of the power station, and provide timely fault warning prompts for the later equipment operation and maintenance, so as to deal with the problem of new energy power generation from the source and achieve better management of new energy power generation;

[0110] Example 2

[0111] like Figure 2 As shown, a 5G private network monitoring system for new energy equipment is based on the above-mentioned 5G private network monitoring method for new energy equipment, and the system includes: an operation stability analysis module, a communication stability analysis module, a risk pre-assessment module, an electrical anomaly analysis module and an intelligent decision-making module;

[0112] The operation stability analysis module is used to analyze whether the operation of the target new energy equipment has been stable in the past preset time period;

[0113] The communication stability analysis module is used to analyze whether the communication of the target new energy equipment is stable within the past preset time period;

[0114] The risk pre-assessment module is used to assess the current operation risk potential of the target new energy equipment based on whether the operation of the target new energy equipment is stable and whether the communication is stable in the past preset time period;

[0115] The electrical anomaly analysis module is used to obtain electrical parameter data of the target new energy equipment in the past preset time period, and obtain the degree of electrical anomaly of the target new energy equipment in the past preset time period based on the electrical parameter data analysis;

[0116] The intelligent decision-making module is used to determine whether a fault warning is needed for the operation of the current target new energy equipment when the target new energy equipment is marked as a risk in its current operating status, based on whether the operation of the target new energy equipment has been stable, whether the communication is stable, and the degree of electrical abnormality in the past preset time period.

[0117] The above formulas are all calculated by removing dimensions and taking numerical values. The formula is a formula that is closest to the actual situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained by simulating a large amount of data.

[0118] In the embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation; the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the method of this embodiment.

[0119] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A 5G private network monitoring method for new energy equipment, characterized in that: include: Step S1: Analyze and obtain whether the operation and communication of the target new energy equipment are stable in the past preset time period, and evaluate the current operation risk hidden danger degree of the target new energy equipment based on whether the operation and communication of the target new energy equipment are stable in the past preset time period; Step S2: obtaining electrical parameter data of the target new energy equipment in the past preset time period, and obtaining the degree of electrical abnormality of the target new energy equipment in the past preset time period based on the electrical parameter data analysis; Step S3: If the target new energy equipment is marked as having a high risk in its current operating state, an analysis is performed based on whether the target new energy equipment has been operating stably, whether its communication is stable, and the degree of electrical abnormality in the past preset time period to determine whether a fault warning is required for the current operation of the target new energy equipment; In step S1, the method of analyzing and obtaining whether the operation of the target new energy equipment in the past preset time period is stable includes: Obtaining the startup records and start-stop records of the target new energy equipment in the past preset time period; based on the acquired startup records and start-stop records of the target new energy equipment in the past preset time period, obtaining the total startup times and total start-stop times of the target new energy equipment in the past preset time period; The ratio of the total number of starts of the target new energy equipment in the past preset time period to the preset time period is marked as the start frequency PD, and the ratio of the total number of starts and stops of the target new energy equipment in the past time period to the preset time period is marked as the start-stop frequency PT; Based on the starting frequency PD and the start-stop frequency PT of the target new energy equipment in the past preset time period, the operation stability index QK of the target new energy equipment in the past preset time period is calculated, and the formula is as follows: Wherein, PDmax and PTmax are the maximum starting frequency and maximum start-stop frequency of the target new energy equipment within the preset time period, a1 and a2 are the weight coefficients of the starting frequency ratio and the start-stop frequency ratio, and the values ​​of a1 and a2 are both greater than 0; γ represents the correction coefficient; Compare the calculated operation stability index of the target new energy equipment in the past preset time period with the preset operation stability index threshold to determine whether the operation of the target new energy equipment in the past preset time period is stable; If the operation stability index of the target new energy equipment in the past preset time period is greater than the preset operation stability index threshold, an operation stability signal is generated; If the operation stability index of the target new energy equipment in the past preset time period is less than or equal to the preset operation stability index threshold, an operation instability signal is generated; In step S1, the method of analyzing and obtaining whether the communication of the target new energy device is stable within the past preset time period includes: According to the type of the past preset time period, the past preset time period is divided into a number of time intervals Δti; i represents the number of the time interval, i=1,2...n; n represents the total number of time intervals included in the preset time period of the corresponding type; Count the number of network disconnections Ci in each time interval Δti, and calculate the average number of network disconnections ΔC in each time interval Δti. The formula is: According to the number of network disconnections Ci in each time interval Δti and the average number of network disconnections ΔC in each time interval Δti, the communication stability index ZQ of the target new energy equipment in the past preset time period is calculated, and the formula is: In the formula, fi represents the weight coefficient of the time zone numbered i, and fi is greater than 0; Compare the communication stability index of the target new energy device obtained by calculation in the past preset time period with the preset communication stability index threshold to determine the communication stability of the target new energy device in the past preset time period; If the communication stability index of the target new energy device in the past preset time period is greater than the preset communication stability index threshold, a communication stability signal is generated; If the communication stability index of the target new energy device in the past preset time period is less than or equal to the preset communication stability index threshold, a communication instability signal is generated; In step S2, electrical parameter data of the target new energy device in the past preset time period is obtained, and the degree of electrical abnormality of the target new energy device in the past preset time period is obtained based on the electrical parameter data analysis; including: Acquire electrical parameter data of the target new energy equipment within a preset time period in the past, and classify the acquired electrical parameter data into m electrical parameter data sets according to the type of the electrical parameters; Compare the electrical parameter values ​​contained in each acquired electrical parameter data set with the preset standard range of the corresponding type of electrical parameters, and count the number of time intervals N1j in which the electrical parameters of the jth type of the target new energy equipment do not meet the preset standard range in the past preset time period; count the number of types N2i of electrical parameters of the target new energy equipment that do not meet the corresponding preset standard range in the i-th time interval in the past preset time period; and count the total number N4i of electrical parameter values ​​of the target new energy equipment in the past preset time period and the number N3i,j of electrical parameter values ​​of the jth type of electrical parameters in the i-th time interval that do not meet the corresponding preset standard range; wherein j=1,2…m; m represents the total number of types of electrical parameters contained in the target new energy equipment; Calculate the electrical abnormality index YD of the target new energy equipment in the past preset time period, the formula is: Wherein, g1 and g2 are both preset weight coefficients greater than 0; In step S3, if the target new energy equipment is marked as having a high risk in its current operating state, an analysis is performed based on whether the target new energy equipment has been operating stably, whether the communication is stable, and the degree of electrical abnormality in the past preset time period to determine whether a fault warning is required for the operation of the current target new energy equipment; including: Obtain the operation stability index QK, communication stability index ZQ and electrical abnormality index YD of the target new energy equipment in the past preset time period; calculate the current operation abnormality trend index KS of the target new energy equipment; the formula is: Wherein, k1, k2 and k3 are the preset weight coefficients of the operation stability index QK, the communication stability index ZQ and the electrical abnormality index YD respectively; the values ​​of k1, k2 and k3 are all greater than 0; Compare the calculated current abnormal operation trend index of the target new energy equipment with the corresponding preset abnormal operation trend index threshold to determine whether a fault warning is required for the operation of the current target new energy equipment; If the current abnormal operation trend index of the target new energy equipment is greater than or equal to the corresponding preset abnormal operation trend index threshold, a signal of operation failure warning is generated; If the current abnormal operation trend index of the target new energy equipment is less than the corresponding preset abnormal operation trend index threshold, a normal operation signal is generated; When a signal of a fault warning of the target new energy equipment is generated, the unique identifier, geographic location information and fault warning signal of the target new energy equipment are sent to the corresponding technician user terminal to notify the corresponding technician to handle it in time.

2. A 5G private network monitoring method for new energy equipment according to claim 1, characterized in that: The types of preset time periods include: one day, one week, one month, one quarter and one year; different types of preset periods all use the logic of peak power consumption, low power consumption and level segment to divide the time interval.

3. A 5G private network monitoring method for new energy equipment according to claim 1, characterized in that: In step S1, the current operation risk level of the target new energy equipment is evaluated based on whether the operation and communication of the target new energy equipment are stable in the past preset time period, including: If the target new energy equipment has unstable operation or unstable communication in the past preset time period, the current operation state of the target new energy equipment is marked as having a high risk; If the target new energy device has been operating stably and communicating stably in the past preset time period, the target new energy device is marked as having low risk in its current operating state.

4. A 5G private network monitoring system for new energy equipment, used to implement a 5G private network monitoring method for new energy equipment according to any one of claims 1 to 3, characterized in that: include: Operation stability analysis module, communication stability analysis module, risk pre-assessment module, electrical anomaly analysis module and intelligent decision-making module; The operation stability analysis module is used to analyze whether the operation of the target new energy equipment has been stable in the past preset time period; The communication stability analysis module is used to analyze whether the communication of the target new energy equipment is stable within the past preset time period; The risk pre-assessment module is used to assess the current operation risk potential of the target new energy equipment based on whether the operation of the target new energy equipment is stable and whether the communication is stable in the past preset time period; The electrical anomaly analysis module is used to obtain electrical parameter data of the target new energy equipment in the past preset time period, and obtain the degree of electrical anomaly of the target new energy equipment in the past preset time period based on the electrical parameter data analysis; The intelligent decision-making module is used to determine whether a fault warning is needed for the operation of the current target new energy equipment when the target new energy equipment is marked as a risk in its current operating status, based on whether the operation of the target new energy equipment has been stable, whether the communication is stable, and the degree of electrical abnormality in the past preset time period.

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