Current transformer connection detection method, device and system and storage medium

Abstract

The invention relates to the technical field of parallel operation energy storage systems, and discloses a current transformer connection detection method, device and system and a storage medium. By controlling the selected phase of the parallel operation energy storage system to independently output power and performing dynamic change adjustment, the relevance of each power variation is analyzed according to the inversion power variation of each energy storage inversion unit, the power variation of the power grid and the constructed detection model, so that the connection state of the CT is judged phase by phase; compared with traditional manual detection or fixed threshold judgment, the method has the advantages that the automation degree is high, positive connection, reverse connection, misconnection and missed connection of the CT can be accurately recognized in real time, abnormity can be found in time, and system faults or performance reduction caused by connection errors are avoided. The intelligent detection technology is adopted, the requirement of traditional auxiliary equipment is avoided, and the detection efficiency and the system reliability are improved.

Description

Technical Field

[0001] This application relates to the technical field of parallel energy storage systems, and particularly to a method, device, system, and storage medium for detecting the connection of current transformers. Background Art

[0002] With the rapid development of energy storage technology, energy storage systems play an important role in distributed energy, microgrids, and user-side load scheduling. In these systems, electricity meters are one of the key components, especially current transformers (CTs), which are not only used to measure the current of the power grid but also to achieve functions such as self-consumption of system power and anti-backflow. However, in actual applications, if the CT of the electricity meter is wrongly connected, it will lead to the acquisition of incorrect data by the energy storage system, which will cause incorrect power scheduling and further abnormal operation of the system.

[0003] Currently, the solutions for detecting whether the CT wiring is normal usually require manual adjustment of the wiring or comparison through a simulated load in the off-grid state, which increases additional complexity and equipment requirements and brings inconvenience to users.

[0004] In addition to the possible wrong connection of the CT wiring, for a parallel system, there may also be a situation where the power line at the grid side of a certain inverter is wrongly connected, that is, the three phases of a certain inverter are not in the same phase sequence as the grid. For example, the L1 phase of inverter B is connected to the L2 phase of the grid. This wrong wiring will cause circulating current between inverters (inverters), and in severe cases, it will even lead to the risk of phase-to-phase short circuit. Summary of the Invention

[0005] The embodiments of this application mainly solve the technical problem of how to intelligently detect the connection status of the current transformers of the electricity meters in the energy storage system and the phase sequence connection status of the current phases between the energy storage inverter units (the connection status of the power lines at the grid side) without relying on auxiliary equipment.

[0006] To solve the above technical problems, a technical solution adopted in an embodiment of the present application is: to provide a method for detecting the connection of a current transformer, which is applied to a parallel energy storage system. The parallel energy storage system includes a plurality of energy storage inverter units, a power grid, and a current transformer. The AC output terminals of each phase of the plurality of energy storage inverter units are connected in parallel and then connected to the power grid. Each phase sampling side of the current transformer is respectively connected to the power grid, and the feedback side is connected to one of the plurality of energy storage inverter units. The method includes: S1. Controlling the selected phase of each energy storage inverter unit to output power separately and performing dynamic change adjustment; S2. Obtaining the inverter power data and grid power data of each energy storage inverter unit; S3. According to the inverter power data and the grid power data, performing power difference calculation processing to obtain the inverter power change amount data and grid power change amount data of each energy storage inverter unit; S4. Constructing a current transformer connection detection model, and based on the inverter power change amount data, grid power change amount data of each energy storage inverter unit and the detection model, obtaining target data; S5. Identifying the connection of the current phase of the current transformer according to the target data; S6. Replacing the selected phase of each energy storage inverter unit and repeating steps S1 - S5 to identify the connection of each phase of the current transformer.

[0007] In some embodiments, step S2 includes: obtaining a data sampling period and a data sampling number according to a preset custom rule; obtaining the inverter power data of each energy storage inverter unit according to the data sampling period and the data sampling number; obtaining the grid power data through the current transformer according to the data sampling period and the data sampling number.

[0008] In some embodiments, step S3 includes: according to the inverter power data, successively calculating the difference between the inverter power at the current acquisition moment and the inverter power at the previous acquisition moment to obtain initial inverter power change amount data; performing screening processing on the initial inverter power change amount data to obtain the inverter power change amount data; according to the grid power data, successively calculating the difference between the grid power at the current acquisition moment and the grid power at the previous acquisition moment to obtain initial grid power change amount data; performing the screening processing on the initial grid power change amount data to obtain the grid power change amount data.

[0009] In some embodiments, step S4 includes: defining a multiple linear regression model according to the inverter power change amount data and the grid power change amount data of each energy storage inverter unit, where the independent variable of the multiple linear regression model is the inverter power change amount of each energy storage inverter unit, and the dependent variable is the grid power change amount; solving each regression coefficient according to the multiple linear regression model and taking each regression coefficient as the target data.

[0010] In some embodiments, step S5 includes: if each regression coefficient satisfies a first preset detection range, determining that the connection state of the current phase of the current transformer is a forward connection; if each regression coefficient satisfies a second preset detection range, determining that the connection state of the current phase of the current transformer is a reverse connection; if each regression coefficient satisfies a third preset detection range, determining that the connection state of the current phase of the current transformer is a wrong connection or a missed connection.

[0011] In some embodiments, step S5 further includes: identifying the phase sequence connection of the current phase between multiple energy storage inverter units according to the target data (identifying the connection of the grid side of the current phase of the energy storage inverter unit according to the target data); step S6 further includes: replacing the selected phase of each energy storage inverter unit and then repeating steps S1 - S5 to identify the phase sequence connection of each phase between multiple energy storage inverter units.

[0012] In some embodiments, if the difference between each regression coefficient satisfies a fourth preset detection range, determining that the phase sequence connection of the current phase between multiple energy storage inverter units is wrongly connected.

[0013] To solve the above technical problems, another technical solution adopted in the embodiments of the present application is: to provide a current transformer connection detection device, the device includes: a control module, the control module is used to control the selected phase of each energy storage inverter unit to independently output power and perform dynamic change adjustment; an acquisition module, the acquisition module is used to acquire the inverter power data and grid power data of each energy storage inverter unit; a calculation module, the calculation module is used to perform power difference calculation processing according to the inverter power data and the grid power data to obtain the inverter power change amount data and grid power change amount data of each energy storage inverter unit; a construction module, the construction module is used to construct a current transformer connection detection model, and based on the inverter power change amount data, grid power change amount data of each energy storage inverter unit and the detection model, obtain target data; an identification module, the identification module is used to identify the connection of the current phase of the current transformer according to the target data.

[0014] To solve the above technical problems, another technical solution adopted in the embodiments of the present application is: to provide a parallel energy storage system, including: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method described above.

[0015] In order to solve the above technical problems, another technical solution adopted in the implementation mode of the present application is: providing a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by the parallel energy storage system, the parallel energy storage system executes the method described above.

[0016] Different from the related art, the present application provides a current transformer connection detection method. By controlling the selected phase of the parallel energy storage system to output power separately and making dynamic changes and adjustments, the correlation between each power change is analyzed according to the inverter power change of each energy storage inverter unit, the power change of the power grid and the constructed detection model, so as to judge the connection status of the CT phase by phase; compared with traditional manual detection or fixed threshold judgment, this method has a high degree of automation and can accurately identify the positive connection, reverse connection, wrong connection and missing connection of the CT in real time, detect abnormalities in time, and avoid system failure or performance degradation due to connection errors. The use of intelligent detection technology eliminates the need for traditional auxiliary equipment and improves detection efficiency and system reliability.

[0017] In a further solution, the detection model uses a multivariate linear regression model, with the inverter power change of each energy storage inverter unit as the independent variable and the grid power change as the dependent variable. By solving each regression coefficient (least square method), it can not only detect the wiring problem of the CT itself, but also effectively diagnose the phase sequence mismatch problem between the inverter and the grid. This dual protection mechanism can fundamentally prevent safety hazards such as circulating current and phase short circuit caused by wiring errors, and raise the system safety level to a new level. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] One or more embodiments are exemplarily described by corresponding drawings, which do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, and the figures in the drawings do not constitute proportional limitations unless otherwise stated.

[0019] Figure 1 It is a structural schematic block diagram of a parallel energy storage system provided in an embodiment of the present application; Figure 2 is a schematic diagram of inverter power change and grid power change provided in an embodiment of the present application; Figure 3 is a flow chart of a current transformer connection detection method provided in an embodiment of the present application; Figure 4 It is a structural schematic block diagram of a current transformer connection detection device provided in an embodiment of the present application; Figure 5 It is a schematic diagram of the hardware structure of a parallel energy storage system for executing a current transformer connection detection method provided in an embodiment of the present application. Detailed implementation manners

[0020] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application.

[0021] It should be noted that if there is no conflict, the various features in the embodiments of the present application can be combined with each other, and all are within the protection scope of the present application. In addition, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different module division from that in the device schematic diagram or a different order from that in the flowchart.

[0022] Unless otherwise defined, all technical and scientific terms used in this specification have the same meaning as commonly understood by those skilled in the technical field to which this application belongs. The terms used in the specification of this application are only for the purpose of describing specific implementation manners, and are not used to limit this application. The term "and / or" used in this specification includes any and all combinations of one or more of the related listed items.

[0023] Please refer to Figure 1 , Figure 1 which is a schematic block diagram of a parallel-connected energy storage system provided by an embodiment of the present application. As Figure 1 shown, taking a three-phase parallel-connected energy storage system as an example, the parallel-connected energy storage system 100 includes: a plurality of energy storage inverter units 10, a power grid 20, and a current transformer (CT) 30. Among them, the energy storage inverter unit 10 includes a first inverter and a second inverter ( Figure 1 INV1 and INV2 of

[0024] In this embodiment, the first inverter 11 and the second inverter 12 are both one of the core components in the parallel energy storage system 100, responsible for converting the direct current stored in the energy storage battery (not shown in the figure) into alternating current suitable for use by the power grid 20 or the load. Each inverter has three-phase outputs (L1, L2, L3), which enables it to supply three-phase alternating current to the power grid 20 or to charge according to the requirements of the power grid 20. Its working principle is as follows: The inverter performs pulse width modulation on the direct current by controlling the power electronic switches to control the output voltage and frequency. When the inverter is in the grid-connected mode, it synchronizes with the voltage and frequency of the power grid; in the off-grid mode, it independently controls the output voltage and frequency. In addition, the inverter also monitors the output power through data acquisition devices (such as electricity meters and current transformers 30) and adjusts the output power according to the power grid demand or energy storage demand.

[0025] The power grid 20 is the energy exchange platform of the parallel energy storage system 100, connecting the parallel energy storage system with the external power network and allowing bidirectional flow of electric energy. The power grid provides the electric energy required by external loads and also accepts the electric energy generated by the parallel energy storage system during discharge. The interconnection relationship between the parallel energy storage system and the power grid is completed through the inverter, and the inverter can adjust the charge and discharge of the system according to the power demand of the power grid. Its working principle is as follows: The power grid provides alternating current to users through its complex power transmission and distribution system. When the parallel energy storage system is operating in grid-connected mode, the inverter outputs the stored electric energy in a form adapted to the power grid, acting as an energy source for the power grid. When the grid load increases or the power demand is too high, the inverter of the parallel energy storage system will supply power to the power grid to help balance the grid load; conversely, when the grid power is in surplus, the parallel energy storage system will charge to store the excess energy.

[0026] The current transformer 30 ( Figure 1 CT in it) is used to measure the current and convert it into a standard signal for use by the monitoring and protection system. Current transformers are usually used in energy storage systems to monitor the current flow direction and magnitude of the power grid and the inverter. Through the current transformer, the system can obtain accurate power data to assist in power scheduling and anomaly detection. Its working principle is as follows: The current transformer provides safe current monitoring by converting large currents into small currents. Its basic principle is through electromagnetic induction, guiding the current to a magnetic core, and then inducing a current proportional to the original current. This current signal is transmitted to the electricity meter or control system through the sensor for processing and monitoring. When the CT wiring direction is correct, the electricity meter can accurately measure the current; if the wiring is incorrect (such as reverse connection or missing connection), the system will obtain incorrect current data, thus affecting power calculation and system scheduling.

[0027] In practical applications, there are the following situations when the wiring of a certain phase of the CT is incorrect. Please refer to Figure 2 , Figure 2It is a schematic diagram of the system inverter power change and grid power change provided by the embodiments of the present application, which can reveal the connection status of the current transformer. Among them, Figure 2 Figure (a) in it describes the system inverter power change and grid power change when a certain phase of the CT is missed or wrongly connected. Figure 2 Figure (b) in it describes the system inverter power change and grid power change when a certain phase of the CT is reversely connected. Figure 2 Figure (c) in it describes the system inverter power change and grid power change when the inverter phase sequence and the grid phase sequence are inconsistent. The abscissa is time T, and the ordinate is power P. For example, in (a), the inverter power changes, while the grid power remains unchanged, which reveals that a certain phase of the CT is missed or wrongly connected. A missed connection means that the wiring of a certain phase of the meter CT is missing (not connected to any phase of the grid). This situation usually causes the parallel energy storage system to be unable to obtain the current signal of this phase, so that the change of the grid power cannot correctly reflect the change of the inverter power. A wrong connection means that a certain phase of the meter CT is wrongly connected to other phases of the grid. When the inverter selects a phase to output power and there is no power output in other phases, no grid current can be collected by this phase of the meter CT. The missed or wrong connection is specifically manifested as the grid power of a certain phase remaining almost unchanged, although the power of this phase of the inverter has changed, resulting in an incorrect system power scheduling. Another example is that in (b), the changes of the inverter power and the grid power are in reverse and proportional, which reveals that a certain phase of the CT is reversely connected. A reverse connection means that the wiring direction of the CT is opposite to the current flow direction. The reversely connected CT will cause the collected current signal direction to be wrong, thus causing an error in power calculation. During the discharge process, the grid power changes in the reverse direction, which may be misjudged as the energy storage system is charging, resulting in the inverter discharging or charging wrongly, and then affecting battery management and grid interaction. Another example is that in (c), the change directions of the inverter power and the grid power are the same, but the change amounts are inconsistent, which reveals the abnormality of the inverter, that is, there is a phase sequence mismatch between a certain inverter and the grid in the grid-connected inverter. This situation may cause the changes of the grid power and the inverter power to be inconsistent. Even if the power of the inverter changes, the change amplitude of the grid power may be small, or the proportional relationship is unbalanced. When the grid phase sequences accessed by different inverters in the parallel system are inconsistent, although the phase difference between phases of a single inverter is normal, due to different phase sequences of the inverters (such as the first inverter is connected to L1\L2\L3, and the second inverter is connected to L2\L3\L1), the change trends of the grid power and the inverter power will deviate. In this case, the changes of the grid power and the inverter power are no longer completely synchronized, resulting in chaotic grid load scheduling and affecting the stability of the system.

[0028] It can be understood that in an energy storage system, the inverter power and the grid power change are strongly correlated. The inverter power is actively controlled by the system, and its change usually directly affects the grid power. Assuming that the load power remains unchanged, the change of the grid power is mainly affected by the inverter power. Under normal circumstances, the inverter dynamically adjusts its output power according to the demand. Therefore, the change trend of the grid power is basically synchronized with the change of the inverter power. Especially in a parallel system, the power changes of multiple inverters will be combined and reflected in the grid power. Since several situations of CT connection errors (such as missing connection, reverse connection, wrong connection) and the inconsistency between the inverter phase sequence and the grid phase sequence will affect the relationship between the inverter power and the grid power, a tool that can effectively analyze the relationship between the inverter power and the grid power change of each inverter in the parallel system is needed. It can be understood that multiple linear regression analysis can construct a linear relationship between the inverter power and the grid power through a model. The goal of the regression model is to determine the degree of influence of the inverter power on the grid power change (i.e., the regression coefficient). Under normal circumstances, the grid power should change in a fixed proportion with the change of the inverter power, that is, the regression coefficient is close to 1. Therefore, through the multiple linear regression method, CT connection errors (such as missing connection, wrong connection, reverse connection) and phase sequence mismatch between the inverter and the grid can be analyzed and detected, because these errors will cause the regression coefficient to deviate significantly from 1, thereby reflecting the inconsistency of power measurement. Regression analysis can automatically detect these deviations and provide quantitative anomaly diagnosis. By continuously collecting data and performing regression analysis, the system can timely detect CT connection errors or phase sequence mismatch between the inverter and the grid, and then realize automatic fault detection and correction.

[0029] For this reason, an embodiment of the present application provides a current transformer connection detection method, which is applied to a parallel energy storage system 100. Please refer to Figure 3 , Figure 3 which is a flowchart of a current transformer connection detection method provided by an embodiment of the present application. As Figure 3 shown, the method includes: S1: Control the selected phase of each energy storage inverter unit to output power separately and perform dynamic change adjustment.

[0030] For a parallel energy storage system, by independently controlling the output power of a certain phase (such as phase L1) of each energy storage inverter unit, the other phases do not output power (such as phases L2 and L3 do not output power), and make its power value change dynamically according to a preset rule (step, ramp or sine wave fluctuation).

[0031] The value of the output power of the energy storage inverter unit can be positive or negative. It is defined that the direction of the energy storage inverter unit delivering power to the grid is the positive direction, and the direction of the grid feeding back power to the energy storage inverter unit is the negative direction.

[0032] S2: Obtain the inverter power data and grid power data of each energy storage inverter unit.

[0033] Obtain the inverter power data and grid power data, including: according to the preset custom rules, obtain the data sampling period and the number of data samplings; according to the data sampling period and the number of data samplings, obtain the inverter power data of each energy storage inverter unit; according to the data sampling period and the number of data samplings, obtain the grid power data of the grid through a current transformer.

[0034] First, set the custom rules in advance according to the system requirements and working environment. Among them, the custom rules include the sampling period and the number of samplings. It can be understood that to obtain the power data, it is necessary to determine the sampling period (such as per second, per minute, etc.), and the sampling period determines the time interval for each data acquisition. For the accurate analysis of the inverter power and grid power, the sampling period should be as short as possible to capture the minute changes in the system operation. Then, it is also necessary to determine the number of samplings. Set the number of data acquisitions required for each detection according to the actual situation (such as 30 times or more). The number of samplings determines the statistical accuracy of the detection result. A larger number of samplings helps to reduce accidental errors and improve the detection accuracy.

[0035] Second, according to the set sampling period and the number of samplings, each energy storage inverter unit monitors its own power data in real time and feeds it back to the energy storage inverter unit acting as the host. The inverter power data is usually in units of three-phase power (L1, L2, L3) and may include forward discharge (output) or reverse charge (input) situations. During the sampling process, after each sampling, the inverter power data will be recorded and saved.

[0036] Third, the CTs collect the currents of each phase of the grid in real time to calculate the power of each phase of the grid. The grid power data reflects the power inflow and outflow situation of the grid and usually includes the three-phase power of the grid. The CTs will monitor the current of the grid and convert it into an appropriate signal for the system to analyze. The magnitude and direction (positive or negative) of the grid power change will directly affect the power dispatching of the energy storage system.

[0037] Finally, at each sampling, the collected inverter power and grid power data will be stored in the local database or the cloud storage system. After each sampling period, the system will record the inverter power and grid power at each moment and perform continuous data acquisition according to the preset rules and number of times until the data analysis requirements are met.

[0038] In this embodiment, through an accurate sampling strategy, it is ensured that the energy storage system can collect inverter power and grid power data in a timely and continuous manner during the detection process. By setting an appropriate sampling period and the number of samplings, it can be ensured that the collected data has sufficient representativeness and accuracy, providing a reliable data basis for the subsequent detection of current transformer connections. This process not only improves the detection accuracy but also effectively reduces errors caused by incomplete data or too low sampling frequency, thereby ensuring the accuracy and reliability of subsequent analysis. In addition, the automation and real-time nature of data collection improve the overall efficiency of the system and reduce the intervention of manual operations.

[0039] S3: According to the inverter power data and grid power data, perform power difference calculation processing to obtain the inverter power change amount data and grid power change amount data of each energy storage inverter unit.

[0040] According to the inverter power data and grid power data of each energy storage inverter unit, perform power difference calculation processing to obtain the inverter power change amount data and grid power change amount data of each energy storage inverter unit, including: According to the inverter power data of each energy storage inverter unit, calculate the difference between the inverter power at the current sampling moment and the inverter power at the previous sampling moment in sequence to obtain the initial inverter power change amount data; perform screening processing on the initial inverter power change amount data to obtain the inverter power change amount data; according to the grid power data, calculate the difference between the grid power at the current sampling moment and the grid power at the previous sampling moment in sequence to obtain the initial grid power change amount data; perform screening processing on the initial grid power change amount data to obtain the grid power change amount data.

[0041] First, each energy storage inverter unit calculates the difference between the inverter power at the current sampling moment and the inverter power at the previous sampling moment according to the collected inverter power data (the inverter power data obtained in step S102), that is: ; Among them, represents the inverter power change amount at the i-th sampling moment of the n-th energy storage inverter unit, represents the inverter power at the i-th sampling moment of the n-th energy storage inverter unit, represents the inverter power of the n-th energy storage inverter unit at the previous sampling.

[0042] Secondly, screen the obtained multiple inverter power change amount data (i.e., the initial inverter power change amount data). The screening conditions can be to eliminate some minor changes (such as fluctuations less than 50W) or noise data to ensure the accuracy of subsequent analysis. After the screening process, the obtained inverter power change amount data will be used for further analysis.

[0043] Next, similar to the calculation of the inverter power change amount, difference calculation is performed on the grid power data. The difference between the grid power at the current acquisition moment and the grid power at the previous acquisition moment is calculated in sequence: ; Among them, represents the grid power change amount at the i-th acquisition moment, represents the grid power at the current acquisition moment, represents the grid power at the previous moment.

[0044] In addition, the obtained multiple grid power change amount data (initial grid power change amount data) is screened. Similar to the screening of inverter power data, some meaningless small changes (such as fluctuations less than 50W) are eliminated. The screened grid power change amount data will more clearly reflect the actual change trend of the grid power.

[0045] Finally, the screened inverter power change amount data and grid power change amount data are stored. For subsequent analysis, the data needs to be classified and marked to ensure that the power data collected each time can correspond to the corresponding timestamp for use in model analysis such as multiple linear regression. It should be noted that when performing the above-mentioned power difference calculation process, the power data and the calculation of the power change amount data can be independently obtained according to the phase number of the energy storage system, that is, when enough data is collected for any phase, the calculation can be performed.

[0046] In this embodiment, by performing difference calculation and screening on the inverter power data and the grid power data, the power change amount data at each acquisition moment can be accurately obtained. By eliminating small fluctuations or noise data, the error can be effectively reduced, ensuring the stability and reliability of the data. In addition, this process provides high-quality input data for subsequent multiple linear regression analysis, ensuring the accuracy and effectiveness of the analysis results. Through the precise processing of the power change amount data, the system can more efficiently detect the connection status of the current transformer, quickly identify any possible incorrect connection or abnormality, and improve the stability and operation efficiency of the energy storage system.

[0047] S4: Construct a current transformer connection detection model, and obtain target data based on the inverter power change amount data, grid power change amount data of each energy storage inverter unit, and the detection model.

[0048] Specifically, it includes: defining a multiple linear regression model according to the inverter power change amount data and the grid power change amount data of each energy storage inverter unit. The independent variable of the multiple linear regression model is the inverter power change amount of each energy storage inverter unit, and the dependent variable is the grid power change amount; according to the multiple linear regression model, each regression coefficient is solved, and each regression coefficient is used as the target data.

[0049] First, a multiple linear regression model needs to be defined based on the data of the inverter power change amount of each energy storage inverter unit and the power change amount data of the power grid. Taking two energy storage inverter units as an example, a binary linear regression model is defined, and its basic form is:

[0050] Among them, is the power change amount of the power grid at the i-th acquisition moment, is the inverter power change amount of the first inverter at the i-th acquisition moment, is the inverter power change amount of the second inverter at the i-th acquisition moment, is the constant term (bias term) of the regression model, and are the regression coefficients, indicating the influence degree of the inverter power change on the power grid power change.

[0051] Secondly, solve the multiple linear regression model to obtain each regression coefficient. For example, use the least squares method to solve each regression coefficient. The least squares method determines the regression coefficients by minimizing the sum of the squares of the errors between the predicted values and the actual values. The steps include: 1) Calculate the error of the regression model for each group of acquisition data; 2) Minimize the sum of the squares of all errors to obtain the regression coefficients of the best fit and ; 3) Calculate the bias term , and use it together with and for the construction of the regression model.

[0052] Finally, take the regression coefficients and as the target data. This coefficient indicates the proportional relationship between the inverter power change of each energy storage inverter unit and the power grid power change. Theoretically, under normal circumstances and should be close to 1, because the changes in inverter power and grid power should be proportional. If and deviate from 1, it may indicate that there are abnormalities in the connection of the CT, such as incorrect connection, missed connection or reverse connection; or the phase sequence mismatch between the inverter and the power grid (that is: the phase sequences between the inverters are different, such as the first inverter is connected to L1\L2\L3, and the second inverter is connected to L2\L3\L1). It should be noted that the solution algorithm in this embodiment is not limited, and it can be the least squares method, or ridge regression, or Lasso regression, etc.

[0053] In this embodiment, a regression model based on the change in inverter power and grid power is constructed, effectively capturing the linear relationship between inverter power and grid power. Through regression analysis, it is possible to accurately determine whether the current transformer connection is normal. The regression coefficients and provide a quantitative standard as target data. When these coefficients deviate from the normal range, the system can automatically identify possible problems such as incorrect connection, missing connection, or abnormal ratio of the current transformer, as well as the phase sequence mismatch problem between the inverter and the grid. This not only improves the automation and accuracy of fault diagnosis but also reduces manual intervention, optimizing the operation efficiency and stability of the system.

[0054] S5: Identify the connection of the current phase of the current transformer according to the target data.

[0055] It can be understood that after obtaining the target data ( and ), the connection status of the current transformer is accurately judged according to this value. In the most ideal case, when and are both 1, the grid power changes by the same amount as the inverter power changes. In actual situations, if the CT is correctly connected, these two coefficients should also be around 1. If there is a large difference, it means the CT is incorrectly connected or missing. For example, when and meet and (, it indicates that the connection status of the current transformer at this time is a forward connection (normal); when and meet and , it indicates that the connection status of the current transformer at this time is a reverse connection; when and meet , it indicates that the connection status of the current transformer at this time is an incorrect connection or a missing connection.

[0056] In addition to being able to detect the wiring problem of the CT itself, the phase sequence mismatch problem between the inverter and the grid can also be effectively diagnosed according to the absolute value of the difference between the regression coefficients. When and meet , it indicates that the phase sequence connection of the grid power line of the energy storage system is incorrect at this time, that is: the three phases of a certain inverter are inconsistent with the phase sequence of the grid, or the phase sequence of the current phase is incorrectly connected between multiple energy storage inverter units of the inverter. It should be noted that the threshold range can be adaptively set according to the actual situation and is not limited here.

[0057] In this embodiment, by precisely inspecting and analyzing the target data and combining multiple preset threshold ranges, it is possible to effectively identify the connection status of the current transformer and the phase sequence mismatch problem between the inverter and the power grid, thereby avoiding equipment failures or unstable operation caused by incorrect connections. By setting different state ranges such as forward connection, reverse connection, incorrect connection, missing connection, and incorrect phase sequence connection, the system can detect and determine the working status of the current transformer or the inverter in real time to ensure its normal operation. In addition, the automatic identification based on the detection results can reduce the risk of manual operation, improve the operation efficiency and safety of the equipment, and is of great significance for the maintenance and management of the power system.

[0058] In some embodiments, the method further includes: giving risk warnings for the above various identification results, such as giving warnings in different display modes / indicator lights; when the grid side of the CT or the inverter is not correctly connected, controlling the alarm unit to give an alarm.

[0059] It can be understood that, based on the identification of the connection status of the current transformer, by further judging the type of inspection result and controlling the indicator light and the alarm system, the visualization and alarm functions of the CT or the inverter are realized. The specific process is as follows: First, through the aforementioned data inspection steps, first judge the connection status of the current transformer (forward connection, reverse connection, incorrect connection) or the incorrect phase sequence connection of the grid side of the inverter, and obtain the corresponding connection type. Secondly, according to the connection type, control the indicator light ( Figure 1 (not shown) to display different modes to help the operator intuitively understand the working status of the current equipment. If it is a forward connection of the CT, control the indicator light to light up in the first display mode (such as green always on) to indicate a normal connection; if it is a reverse connection of the CT, control the indicator light to light up in the second display mode (such as red flashing) to remind the user of a reverse connection; if it is an incorrect connection or a missing connection of the CT, control the indicator light to light up in the third display mode (such as yellow warning light always on) to warn that there is an error in the connection; if it is an incorrect phase sequence connection of the inverter, control the indicator light to light up in the fourth display mode (such as blue flashing) to indicate that the phase sequence wiring of the grid side of the inverter is incorrect. In addition, when judging the type, if it is a reverse connection, incorrect connection or missing connection of the CT, or an incorrect phase sequence connection of the grid side of the inverter, then trigger the alarm unit ( Figure 1 (not shown) to give an alarm. The alarm unit can remind the staff through sound or other warning signals to ensure that the connection problem is discovered and corrected in time. In addition, the alarm system can also set different alarm levels according to different severities. For example, a reverse connection can issue a relatively light alarm, while an incorrect connection or an incorrect phase sequence connection may issue a relatively strong alarm. Finally, through the feedback of the indicator light and the alarm, the maintenance personnel can quickly judge whether there is a wiring problem with the current transformer, and then take appropriate measures, such as adjusting the wiring or conducting an inspection, to ensure the stable operation of the equipment.

[0060] In this embodiment, by monitoring and judging the connection state of the current transformer in real time, different connection states can be effectively presented to the operator in a visual way. Through different display modes of the indicator lights, the staff can intuitively understand the operating state of the equipment, discover problems in time and make adjustments, reducing the incidence of human errors. In addition, the addition of the alarm unit further improves the security of the system, and can quickly issue a warning in the case of non-normal connection, ensuring the stability of the current transformer and the entire system. This method not only improves the equipment management efficiency, but also enhances the response ability of the operator, reducing the occurrence of potential faults and accidents.

[0061] In some embodiments, the method further includes: uploading the inspection result to the server, so that after receiving the inspection result, the server performs data parsing to obtain the parsing result, and generates a connection detection report of the current transformer according to the parsing result.

[0062] First, in the foregoing steps, the system has inspected the connection state of the current transformer and obtained the corresponding results. The inspection results are sorted according to a predetermined data format to ensure the integrity and consistency of the data. Then, through a network interface (such as HTTP, FTP, etc.), the formatted data is uploaded to the server. Among them, the transmission method can adopt protocols such as HTTP, FTP, etc. to ensure the integrity and security of the data.

[0063] Second, after the server receives the uploaded inspection result data, it first performs data integrity and validity verification to ensure that the data has not been tampered with or lost. Subsequently, using predefined data parsing rules, the original data is converted into structured information, such as JSON or XML format, for subsequent processing.

[0064] Third, according to the parsing result, the connection states of the current transformers are classified and counted, and the quantity and proportion of various connection states are analyzed. According to the analysis results, a connection detection report of the current transformer is automatically generated. The report content includes: basic information: detection time, detection personnel, equipment number, etc.; detection results: statistical data and analysis of various connection states; recommended measures: corresponding rectification suggestions for the discovered problems.

[0065] Finally, the generated detection report is stored in the database or file system of the server to ensure long-term preservation and backup of the data. According to needs, the report can also be sent to relevant personnel, such as equipment maintenance personnel, management, etc. by email, text message or other means. After receiving the report, the relevant personnel should rectify the problems in the report and feedback the rectification results to the server. After receiving the rectification feedback, the server updates the records in the database to keep the data up-to-date and accurate.

[0066] In this embodiment, by uploading the inspection result of the current transformer connection status to the server for data parsing and generating a detailed inspection report, it is possible to achieve comprehensive monitoring and management of the device status. Automated data processing and report generation improve work efficiency and reduce errors and omissions in manual operations. At the same time, the report storage and distribution mechanism ensures the timely transmission and sharing of information, facilitating relevant personnel to promptly understand the device status, take necessary maintenance measures, and ensure the safe and stable operation of the power system.

[0067] The embodiment of the present application provides a method for detecting the connection of a current transformer. Through the calculation of the power difference between the inverter power data and the grid power data and the construction of a regression model, it is possible to accurately identify the connection status of the current transformer in the energy storage system. This method can monitor the connection of the current transformer in real time, promptly detect abnormalities, and avoid system failures or performance degradation caused by incorrect connections. By adopting intelligent detection technology, the need for traditional auxiliary equipment is eliminated, improving the detection efficiency and system reliability. At the same time, through different detection range and type judgments, it is possible to accurately distinguish the forward connection, reverse connection, incorrect connection, or missing connection of the CT, as well as the incorrect connection of the grid-side phase sequence of the inverter, providing an important basis for system maintenance and fault troubleshooting, and having significant practical value and economic benefits. It should be noted that the method for detecting the connection of the current transformer provided in this embodiment can be applied to three-phase, two-phase, and single-phase energy storage systems, and is not limited to the three-phase energy storage system exemplified above. In actual applications, a regression model can be adaptively constructed according to the type of the energy storage system.

[0068] Based on the method for detecting the connection of the current transformer provided in the above embodiment, the embodiment of the present application further provides a device for detecting the connection of the current transformer. Please refer to Figure 4 , Figure 4 which is a structural schematic block diagram of the device for detecting the connection of the current transformer. As Figure 4 shown, the device 200 includes: a control module 250, an acquisition module 210, a calculation module 220, a construction module 230, and an identification module 240.

[0069] Among them, the control module 250 is used to control the selected phase of each energy storage inverter unit to independently output power and perform dynamic change adjustment; the acquisition module 210 is used to acquire the inverter power data and grid power data of each energy storage inverter unit; the calculation module 220 is used to perform power difference calculation processing based on the inverter power data and grid power data to obtain the inverter power change data and grid power change data of each energy storage inverter unit; the construction module 230 is used to construct a current transformer connection detection model, and based on the inverter power change data, grid power change data of each energy storage inverter unit and the detection model, obtain target data; the identification module 240 is used to identify the connection of the current phase of the current transformer according to the target data.

[0070] It should be noted that the above current transformer connection detection device can execute the current transformer connection detection method provided by the embodiments of the present application, and has corresponding functional modules and beneficial effects for executing the method. For technical details not described in detail in the embodiments of the current transformer connection detection device, reference may be made to the current transformer connection detection method provided by the embodiments of the present application.

[0071] The embodiments of the present application also provide a parallel energy storage system. Please refer to Figure 5 , which shows a schematic hardware structure diagram of a parallel energy storage system capable of executing the method described in the above embodiments. The parallel energy storage system 100 includes: at least one processor 310; and a memory 320 communicatively connected to the at least one processor 310. Figure 5 Here, one processor 310 is taken as an example. The memory 320 stores instructions executable by the at least one processor 310. The instructions are executed by the at least one processor 310 so that the at least one processor 310 can execute the current transformer connection detection method described in the above embodiments. The processor 310 and the memory 320 can be connected by a bus or other means. Figure 5 Here, connection by a bus is taken as an example.

[0072] As a non-volatile computer-readable storage medium, the memory 320 can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as program instructions / modules corresponding to the current transformer connection detection method in the embodiments of the present application. By running the non-volatile software programs, instructions, and modules stored in the memory 320, the processor 310 executes various functional applications and data processing of the server, that is, implements the current transformer connection detection method described in the above embodiments.

[0073] The memory 320 can include a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created according to the use of the computing device, etc. In addition, the memory 320 can include a high-speed random access memory, and can also include non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices. In some of these embodiments, the memory 320 can optionally include a memory remotely provided relative to the processor 310, and these remote memories can be connected to the computing device through a network. Examples of the above networks include, but are not limited to, the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0074] The one or more modules are stored in the memory 320 and, when executed by the one or more processors 310, perform the current transformer connection detection method described in the above embodiments.

[0075] It should be noted that the current transformer connection detection method provided in the above embodiments is applied to the main controller of the parallel energy storage system. Among them, the main controller can be integrated into the energy storage inverter unit that serves as the host among multiple energy storage inverter units, or can exist independently of multiple energy storage inverter units. It can be understood that when the main controller is integrated into a certain energy storage inverter unit, this energy storage inverter unit is called the host, and other energy storage inverter units serve as slaves, and the above current transformer connection detection method is executed through the main controller in the host. When the main controller exists independently of multiple energy storage inverter units, the main controller can be independent hardware (such as PLC, industrial computer, dedicated controller), and interacts with all energy storage inverter units through a communication network (such as CAN, Modbus, Ethernet) to execute the above current transformer connection detection method.

[0076] The above product can execute the method provided in the embodiments of the present application, and has the corresponding functional modules and beneficial effects for executing the method. For technical details not described in detail in this embodiment, reference can be made to the current transformer connection detection method described in the embodiments of the present application.

[0077] The embodiments of the present application also provide a non-volatile computer-readable storage medium. The non-volatile computer-readable storage medium stores computer-executable instructions, and these computer-executable instructions are executed by one or more processors so that the at least one processor can execute the current transformer connection detection method described in the above embodiments. For example, the non-volatile computer-readable storage medium can be a Read-Only Memory (ROM), a Random Access Memory (RAM), a Compact Disc Read-Only Memory (CDROM), magnetic tape, floppy disk, and optical data storage device, etc.

[0078] It should be noted that the above-described embodiments are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0079] Through the description of the above embodiments, those of ordinary skill in the art can clearly understand that each embodiment can be implemented by means of software plus a general hardware platform, and of course, it can also be implemented by hardware. Those of ordinary skill in the art can understand that all or part of the processes in the above-described method embodiments can be completed by instructing relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above-described method embodiments. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM), etc.

[0080] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; under the idea of the present application, the technical features in the above embodiments or different embodiments can also be combined, and the steps can be implemented in any order, and there are many other variations in different aspects of the present application as described above. For the sake of brevity, they are not provided in detail; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A current transformer connection detection method, applied to a parallel energy storage system, the parallel energy storage system comprises a plurality of energy storage inverter units, a power grid and a current transformer, each phase AC output end of the plurality of energy storage inverter units is connected in parallel to the power grid, each phase sampling side of the current transformer is respectively connected to the power grid, and the feedback side is connected to one of the plurality of energy storage inverter units, characterized in that: The method comprises the following steps: S1. Control the selected phase of each energy storage inverter unit to output power individually and adjust it dynamically; S2. Obtain the inverter power data and grid power data of each energy storage inverter unit; S3. According to the inverter power data and the grid power data, the power difference is calculated and processed to obtain the inverter power change data and the grid power change data of each energy storage inverter unit; S4. construct a current transformer connection detection model, and obtain target data based on the inverter power change data of each energy storage inverter unit, the grid power change data and the detection model; S5. Identify the connection of the current transformer current phase according to the target data; S6. Replace the selected phase of each energy storage inverter unit and repeat steps S1-S5 to identify the connection of each phase of the current transformer.

2. The current transformer connection detection method according to claim 1, characterized in that: The step S2 comprises: According to the preset custom rules, the data sampling period and data sampling times are obtained; According to the data sampling period and the data sampling times, acquiring the inverter power data of each energy storage inverter unit; The power grid power data is acquired through the current transformer according to the data sampling period and the data sampling times.

3. The current transformer connection detection method according to claim 1, characterized in that: The step S3 comprises: According to the inverter power data, the difference between the inverter power at the current collection time and the inverter power at the previous collection time is calculated in sequence to obtain initial inverter power change data; Screening the initial inverter power variation data to obtain the inverter power variation data; According to the power grid data, the difference between the power grid power at the current collection time and the power grid power at the last collection time is calculated in sequence to obtain initial power grid power change data; The initial power grid power variation data is subjected to the screening process to obtain the power grid power variation data.

4. The current transformer connection detection method according to claim 1, characterized in that: The step S4 comprises: According to the inverter power variation data of each energy storage inverter unit and the grid power variation data, a multiple linear regression model is defined, wherein the independent variable of the multiple linear regression model is the inverter power variation of each energy storage inverter unit, and the dependent variable is the grid power variation; According to the multivariate linear regression model, each regression coefficient is solved, and each regression coefficient is used as the target data.

5. The current transformer connection detection method according to claim 4, characterized in that: The step S5 comprises: If the regression coefficients satisfy the first preset detection range, determining that the connection state of the current phase of the current transformer is a forward connection; If the regression coefficients satisfy a second preset detection range, determining that the connection state of the current phase of the current transformer is a reverse connection; If the regression coefficients satisfy a third preset detection range, it is determined that the connection state of the current phase of the current transformer is an incorrect connection or a missing connection.

6. The current transformer connection detection method according to claim 4, characterized in that: The step S5 also includes: identifying the phase sequence connection of the current phase between multiple energy storage inverter units according to the target data; the step S6 also includes: replacing the selected phase of each energy storage inverter unit and repeating steps S1-S5 to identify the phase sequence connection of each phase between multiple energy storage inverter units.

7. The current transformer connection detection method according to claim 6, characterized in that: If the absolute value of the difference between the regression coefficients satisfies the fourth preset detection range, it is determined that the phase sequence of the current phase between the multiple energy storage inverter units is incorrectly connected.

8. A current transformer connection detection device, characterized in that: The device comprises: A control module, the control module is used to control the selected phase of each energy storage inverter unit to output power individually and perform dynamic change adjustment; An acquisition module, the acquisition module is used to acquire the inverter power data and grid power data of each energy storage inverter unit; A calculation module, the calculation module is used to perform power difference calculation processing according to the inverter power data and the grid power data, and obtain inverter power change data and grid power change data of each energy storage inverter unit; A construction module, the construction module is used to construct a current transformer connection detection model, and obtain target data based on the inverter power change data of each energy storage inverter unit, the grid power change data and the detection model; An identification module is used to identify the connection of the current phase of the current transformer according to the target data.

9. A parallel energy storage system, characterized in that: include: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 7.

10. A non-volatile computer-readable storage medium, characterized in that: The non-volatile computer-readable storage medium stores computer-executable instructions. When the computer-executable instructions are executed by the parallel energy storage system, the parallel energy storage system executes the method according to any one of claims 1 to 7.

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