Low-voltage photovoltaic grid-connected circuit breaker detection method

Abstract

The invention relates to a detection method for a low-voltage photovoltaic grid-connected circuit breaker, and the method carries out the real reproduction of the operation environment of the circuit breaker based on the large-range power linear amplification technology of current common-conduction and non-common-return. A measurement data simulation technology based on a deviation model is adopted, and high-precision output of voltage and current in the test process is ensured through a software and hardware two-stage correction method; through a residual current equivalent test technology, closed-loop automatic test of a residual current protection function is carried out. Through a software and hardware two-stage correction method, the high precision of voltage and current measurement is ensured, and the reliability of a detection result is improved. And through a residual current equivalent test technology, many limitations of traditional test equipment are solved, system integration and automatic test are facilitated, and the test cost is reduced.

Description

Technical Field

[0001] The invention belongs to the technical field of safety protection of low-voltage photovoltaic grid-connected systems, and in particular to a detection method for a low-voltage photovoltaic grid-connected circuit breaker. Background Art

[0002] With the continuous advancement of technology and the growing demand for applications, low-voltage photovoltaic grid-connected circuit breakers have developed many new functions based on traditional circuit breakers. These new functions enhance the intelligence and comprehensive performance of circuit breakers, but also bring new challenges and requirements to detection technology. At present, although there are some detection methods for low-voltage intelligent circuit breakers, there are still limitations in the comprehensive evaluation of the functions of low-voltage photovoltaic grid-connected circuit breakers due to the lack of measurement accuracy, the large size of traditional residual current test equipment, relatively low accuracy, and difficulty in system integration. And the detection means for new functions are relatively insufficient. This leads to the fact that in practical applications, it may not be possible to comprehensively and accurately evaluate the comprehensive performance of low-voltage photovoltaic grid-connected circuit breakers, thus affecting the safe and stable operation of the power system. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art and propose a low-voltage photovoltaic grid-connected circuit breaker detection method, which is based on a large-range power linear amplification technology with common current conduction but not common return, a measurement data simulation technology based on a deviation model, and a residual current equivalent test technology. By synchronously injecting voltage and current of different loops into the copper rod, and using software and hardware two-level correction methods, the real reproduction of the operating environment of the low-voltage photovoltaic grid-connected circuit breaker and the high-precision output of voltage and current are achieved.

[0004] The present invention solves the technical problem by adopting the following technical solutions:

[0005] A low-voltage photovoltaic grid-connected circuit breaker detection method comprises the following steps:

[0006] Step 1: Based on the large-range power linear amplification technology with common current conduction but not common return, the circuit breaker operating environment is truly reproduced;

[0007] Step 1.1. Select a high-performance power amplifier to ensure that the range and accuracy of its output voltage and current meet the test requirements;

[0008] Step 1.2, program and calibrate the power amplifier to set the appropriate output current waveform and amplitude;

[0009] Step 1.3: Prepare the copper rod and make sure it has good conductivity and can withstand the current and voltage in the test;

[0010] Step 1.4, the power amplifier synchronously injects currents of different loops into the copper rod according to preset parameters;

[0011] Step 1.5, equip a data acquisition system to monitor and record the current and voltage waveforms and the response of the device under test in real time;

[0012] Step 1.6: Process and analyze the real-time monitoring data;

[0013] Step 2: Using the measurement data simulation technology based on the deviation model, the high-precision output of voltage and current during the test is ensured through the two-level correction method of software and hardware;

[0014] Step 3: Perform closed-loop automatic test of the residual current protection function through the residual current equivalent test technology.

[0015] Moreover, the specific implementation method of step 1.6 is: extracting real-time monitoring and recording the key parameters in the current and voltage waveforms and the response of the equipment under test, analyzing the performance of the equipment under test under different working conditions, and evaluating the tolerance, response speed and stability; proposing improvement suggestions or optimization plans based on the analysis results to improve the performance of the equipment under test or the accuracy of the test method; among which the tolerance is mainly achieved by optimizing the insulating materials and improvements, the response speed is mainly achieved by conducting FSM breaking principle analysis, step-by-step breaking method analysis, etc., and the stability is mainly achieved by carefully designing the electrodes and gaps to change the internal structure optimization, and at the same time designing a reasonable shell structure to ensure that the equipment can withstand the external pressure during the high-voltage test.

[0016] Moreover, the hardware correction method in step 2 is: correction based on a fast-response zero-static-error feedback hardware loop, and the software correction method is: software correction based on a measurement data simulation technology of a deviation model.

[0017] Moreover, the specific implementation method of the correction based on the fast-response zero-static-error feedback hardware loop is: according to the detection result of the fast-response zero-static-error feedback hardware loop, adjust the proportional gain parameter to optimize the control performance; verify the effect of the zero-static-error feedback according to the steady-state output under different conditions; and verify the compliance of the performance indicators of the fast response and zero-static-error feedback by performing performance tests on the hardware loop under different working conditions.

[0018] Moreover, the specific implementation method of the software correction using the measurement data simulation technology based on the deviation model is as follows: constructing a deviation model, designing model parameters, and performing model training; predicting the measurement data through the deviation model, and comparing it with the actual measurement value, calculating the deviation amount, and identifying the source and type of the deviation; adjusting the model parameters to reduce the deviation based on the deviation analysis results, and integrating the correction algorithm in the software, receiving real-time measurement data, and calculating the correction value based on the deviation model.

[0019] Moreover, the specific implementation method of step 3 is: using a high-precision power source device to generate an analog signal that is identical to the residual current waveform that appears in an actual low-voltage photovoltaic grid-connected system, and recording the data, analyzing whether the behavior of the circuit breaker during the test meets the standard requirements based on the recorded data, and evaluating the performance of the circuit breaker in residual current protection to see whether it meets the requirements of relevant standards and specifications.

[0020] The advantages and positive effects of the present invention are:

[0021] The present invention is based on a large-range power linear amplification technology with common conduction but not common return of current to truly reproduce the operating environment of the circuit breaker; adopts a measurement data simulation technology based on a deviation model, and ensures high-precision output of voltage and current during the test through a two-level correction method of software and hardware; and performs closed-loop automatic testing of the residual current protection function through a residual current equivalent test technology. The present invention ensures high-precision voltage and current measurement and improves the reliability of the test results through a two-level correction method of software and hardware. And through the residual current equivalent test technology, many limitations of traditional test equipment are solved, system integration and automated testing are facilitated, and test costs are reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A software correction flow chart for the present invention;

[0023] Figure 2 This is a data preprocessing diagram of the present invention;

[0024] Figure 3 This is a clear analysis diagram of the data of the present invention. DETAILED DESCRIPTION

[0025] The present invention is further described in detail below with reference to the accompanying drawings.

[0026] A low-voltage photovoltaic grid-connected circuit breaker detection method comprises the following steps:

[0027] Step 1: Based on the large-range power linear amplification technology with common current conduction but not common return, the circuit breaker operating environment is truly reproduced.

[0028] The idea of ​​this step is: the common conduction of current but not the common return uses a common conductive channel (such as a copper rod) to transmit the current of different loops, but these currents are electrically isolated, that is, they do not share the same loop path, to achieve efficient, large-scale power amplification and control. Based on the large-scale power linear amplification technology of current co-conduction but not common return, a power amplifier is used to generate a precisely controlled current waveform. The current waveform is injected into the device to be tested (such as a low-voltage photovoltaic grid-connected circuit breaker) through a common conductive channel (such as a copper rod). By independently controlling the current, accurate synchronization and linear amplification of the currents of different loops are achieved, thereby simulating various working conditions in actual operation. The key to the large-scale power linear amplification technology based on current co-conduction but not common return is to ensure that the currents of different loops are electrically isolated while being transmitted through a common conductive channel.

[0029] Step 1 includes the following steps:

[0030] Step 1.1. Select a high-performance power amplifier and ensure that its output voltage and current range and accuracy meet the test requirements.

[0031] Step 1.2: Program and calibrate the power amplifier to set the appropriate output current waveform and amplitude.

[0032] Step 1.3: Prepare the copper rod, making sure it has good conductivity and can withstand the current and voltage in the test.

[0033] Step 1.4: The power amplifier synchronously injects currents of different loops into the copper rod according to preset parameters.

[0034] Step 1.5: Equip a data acquisition system, such as an oscilloscope, data logger, etc., to monitor and record the current and voltage waveforms and the response of the device under test in real time.

[0035] According to the principle of common conduction but not common return of current, the circuit structure is designed, and high-performance insulating materials and isolation devices, such as insulators and isolation transformers, are used to achieve electrical isolation between different circuits; and suitable filtering circuits and protection circuits are designed to ensure the stability of output current and protect the equipment under test.

[0036] Step 1.6: Process and analyze the real-time monitoring data.

[0037] Extract key parameters, such as the peak value, effective value, waveform distortion rate, etc. of current and voltage; analyze the performance of the equipment under test under different working conditions, and evaluate its tolerance, response speed, and stability. Propose improvement suggestions or optimization plans based on the analysis results to improve the performance of the equipment under test or the accuracy of the test method. The tolerance is mainly achieved through the optimization of insulating materials and improvements, the response speed is mainly achieved through the analysis of FSM breaking principles and step-by-step breaking methods, and the stability is mainly achieved through the careful design of electrodes and gaps to optimize the internal structure, while designing a reasonable shell structure to ensure that the equipment can withstand the external pressure during the high-voltage test.

[0038] Step 2: Using the measurement data simulation technology based on the deviation model, the high-precision output of voltage and current during the test is ensured through the two-level correction method of software and hardware.

[0039] The hardware correction method is: correction based on a fast-response zero-error feedback hardware loop. Zero-error feedback uses a specific control strategy to make the output equal to the given value of the system in steady state, and the deviation between the two is zero.

[0040] The specific implementation method for correction based on the fast-response zero-static-error feedback hardware loop is as follows: according to the detection result of the fast-response zero-static-error feedback hardware loop, adjust the proportional gain parameters to optimize the control performance; verify the effect of the zero-static-error feedback according to the steady-state output under different conditions; and verify whether the performance indicators of the fast response and zero-static-error feedback meet the standards by performing performance tests on the hardware loop under different working conditions.

[0041] Step 2.1: Clarify the performance indicators such as control accuracy and response speed that the hardware loop needs to achieve according to the requirements;

[0042] Step 2.2, debug the hardware circuit; under the condition of no input signal or only adding a fixed level signal, perform static debugging on the hardware circuit to determine whether the working state is normal;

[0043] Step 2.3: On the basis of static debugging, add appropriate input signals to dynamically debug the hardware circuit, and use tools such as oscilloscopes to output signal waveforms, amplitudes, frequencies and other parameters;

[0044] Step 2.4: According to the debugging results of the hardware loop, adjust the proportional gain and other parameters to optimize the control performance;

[0045] Step 2.5: Verify the effect of zero-static-error feedback based on the steady-state output under different conditions;

[0046] Step 2.6: Perform performance tests on the hardware circuit under different working conditions to verify whether its performance indicators of fast response and zero static error feedback meet the standards;

[0047] Step 2.7: Conduct in-depth analysis of the test data to evaluate the performance indicators of the hardware loop, such as control accuracy and response speed.

[0048] Step 2.8: According to the results of performance verification and data analysis, make corresponding corrections and improvements to the hardware circuit.

[0049] The software correction method is to perform software correction based on the measurement data simulation technology of the deviation model. The deviation model reflects the error source, distribution law and dynamic change in the actual measurement data, and generates simulation data that is similar to the real measurement data but contains preset or random deviations. The simulation data is used to test and analyze the performance of the circuit breaker under various deviation conditions to ensure its reliability and stability in complex environments.

[0050] The specific implementation method of software correction based on the measurement data simulation technology of the deviation model is: construct a deviation model, design model parameters, and perform model training, predict the measurement data through the deviation model, and compare it with the actual measurement value, calculate the deviation amount, and identify the source and type of the deviation; according to the deviation analysis results, adjust the model parameters to reduce the deviation, and integrate the correction algorithm in the software, receive real-time measurement data, and calculate the correction value according to the deviation model.

[0051] Step 2.9, collect real-time data of key parameters such as current and voltage from the low-voltage photovoltaic grid-connected circuit breaker test system;

[0052] Step 3.10: Clean, denoise and standardize the collected data;

[0053] Step 2.11: Build a bias model:

[0054] Step 2.12: Select an appropriate deviation model based on the characteristics of the data and the detection requirements; the deviation model can be a linear model or polynomial model based on statistics, or a complex model based on machine learning.

[0055] Step 2.13, estimate model parameters by least squares method, maximum likelihood estimation and other methods;

[0056] Step 2.14: Evaluate the generalization ability of the model through cross-validation (such as K-fold cross-validation) to ensure that the model performs well on unknown data;

[0057] Step 2.15: Predict the measured data through the deviation model, compare it with the actual measured value, and calculate the deviation;

[0058] Step 2.16: Conduct in-depth analysis of the calculated deviations to identify the sources and types of deviations (such as systematic errors, random errors, environmental interference, etc.).

[0059] Step 2.17, perform software correction, and adjust model parameters to reduce the deviation according to the deviation analysis results;

[0060] Step 2.18: Integrate a correction algorithm in the software, which can receive real-time measurement data and calculate correction values ​​based on the deviation model.

[0061] Step 2.19: Verify and evaluate the modified software using simulated data to check whether the modified algorithm effectively reduces the deviation;

[0062] Step 2.20: Compare the test results before and after correction to evaluate whether the correction effect meets the detection requirements.

[0063] Step 2.21: Based on the verification and test results, tune the parameters in the correction algorithm to further optimize the correction effect.

[0064] Step 3: Perform closed-loop automatic test of the residual current protection function through the residual current equivalent test technology.

[0065] A high-precision power source device is used to generate a simulated signal that is highly similar to the residual current waveform that appears in the actual low-voltage photovoltaic grid-connected system, and the data is recorded. Based on the recorded data, it is analyzed whether the behavior of the circuit breaker during the test meets the standard requirements, and the performance of the circuit breaker in residual current protection is evaluated to see whether it meets the relevant standards and specifications.

[0066] Step 3.1: Prepare relevant test equipment according to test requirements, including: high-precision power source, residual current detection device, oscilloscope, power data acquisition device, etc.;

[0067] Step 3.2: Connect the high-precision power source, low-voltage photovoltaic grid-connected circuit breaker, oscilloscope and other equipment accurately according to the test requirements; set the output parameters of the high-precision power source, including voltage, current and waveform, according to the test requirements.

[0068] Step 3.3: Select a suitable residual current waveform for simulation according to the actual situation of the photovoltaic grid-connected system. Common waveforms include sine waves, square waves, etc. The residual current waveform simulation includes: setting the amplitude of the residual current according to the protection threshold of the circuit breaker; setting the frequency and duration of the waveform to ensure that the protection response time of the circuit breaker can be fully tested.

[0069] Step 3.4: Output the simulated residual current waveform through a high-precision power source, and start the oscilloscope and the power data acquisition device to record at the same time.

[0070] Step 3.5: Based on data recording and analysis, observe and record the waveform changes of the residual current during the simulation process through an oscilloscope; collect parameter data such as voltage and current during the test through an electrical quantity data acquisition device; compare the simulated waveform with the expected waveform to evaluate the protection response time and accuracy of the circuit breaker to the residual current. At the same time, analyze whether the behavior of the circuit breaker during the test meets the standard requirements.

[0071] Step 3.6: Based on the test data and waveform analysis, evaluate the performance of the circuit breaker in residual current protection and determine whether it meets the requirements of relevant standards and specifications.

[0072] According to the above-mentioned low-voltage photovoltaic grid-connected circuit breaker detection method, the steps of the present invention are described through the following embodiments to verify the effect of the present invention.

[0073] Embodiment: The measurement data simulation technology based on the deviation model is adopted, and the high-precision output of voltage and current during the test process is ensured through a two-level correction method of software and hardware.

[0074] The hardware correction method includes the following steps:

[0075] Step 1: Clarify the performance indicators such as control accuracy and response speed that the hardware loop needs to achieve according to the requirements;

[0076] Step 2: Debug the hardware circuit; statically debug the hardware circuit without adding input signal or only adding fixed level signal to determine whether the working status is normal; based on static debugging, add appropriate input signal to dynamically debug the hardware circuit, and use tools such as oscilloscope to output the waveform, amplitude, frequency and other parameters of the signal;

[0077] Step 3: According to the debugging hardware loop results, adjust the proportional gain and other parameters to optimize the control performance;

[0078] Step 4: Verify the effect of zero-static-error feedback based on the steady-state output under different conditions;

[0079] Step 5: Perform performance tests on the hardware circuit under different working conditions to verify whether its performance indicators of fast response and zero static error feedback meet the standards;

[0080] Step 6: Conduct in-depth analysis of the test data to evaluate the performance indicators of the hardware loop, such as control accuracy and response speed.

[0081] Step 7: Based on the results of performance verification and data analysis, make corresponding corrections and improvements to the hardware circuit.

[0082] Figure 1 As shown, the software correction method includes the following steps:

[0083] Step 1: Collect real-time data of key parameters such as current and voltage from the low-voltage photovoltaic grid-connected circuit breaker test system;

[0084] Step 2: Clean, denoise and standardize the collected data. The process of re-examining and verifying the data, deleting duplicate information, correcting erroneous information, and ensuring data consistency. Remove the unit restrictions of the data and convert it into dimensionless pure values ​​to avoid certain features of the data from taking the lead due to different dimensions. The most typical one is data normalization, which is to uniformly map the data to the interval [0, 1];

[0085] Now combined Figure 2 and Figure 3 , the data preprocessing is explained. First, the data stream is divided into data blocks of equal size, and The data blocks form a sliding window, and the candidate outliers in the previous sliding window are added to the current sliding window to obtain the data set D; in the second stage, the data set D is first normalized, and then anomaly detection is performed based on the proposed local vector dot product density LDVP and the new decision criterion to obtain the candidate outliers of the current window data set, and the candidate outliers are verified. If and only if the candidate outlier point has been verified for the number of times in the continuous verification is equal to the verification threshold Only when these candidate outliers are identified as real outliers are saved in the outlier database.

[0086] Step 3: Build a bias model: Select an appropriate bias model based on the characteristics of the data and detection requirements;

[0087] Step 4: Estimate model parameters by least squares method, maximum likelihood estimation and other methods;

[0088] Step 5: Evaluate the generalization ability of the model through cross-validation (such as K-fold cross-validation) and other methods to ensure that the model performs well on unknown data;

[0089] Step 6: Predict the measured data through the deviation model, compare it with the actual measured value, and calculate the deviation;

[0090] Step 7: Conduct in-depth analysis of the calculated deviations to identify the sources and types of deviations (such as systematic errors, random errors, environmental interference, etc.).

[0091] Step 8: Perform software correction and adjust model parameters to reduce deviation according to the deviation analysis results;

[0092] Step 9: Integrate a correction algorithm in the software that receives real-time measurement data and calculates correction values ​​based on the deviation model.

[0093] Step 10: Verify and evaluate the modified software using simulated data to check whether the modified algorithm effectively reduces the deviation;

[0094] Step 11: Compare the test results before and after correction to evaluate whether the correction effect meets the detection requirements.

[0095] Step 12: Based on the verification and test results, tune the parameters in the correction algorithm to further optimize the correction effect.

[0096] The present invention is based on a large-range power linear amplification technology with common conduction but not common return of current to truly reproduce the operating environment of the circuit breaker; adopts a measurement data simulation technology based on a deviation model, and ensures high-precision output of voltage and current during the test through a two-level correction method of software and hardware; and performs closed-loop automatic testing of the residual current protection function through a residual current equivalent test technology. The present invention ensures high-precision voltage and current measurement and improves the reliability of the test results through a two-level correction method of software and hardware. And through the residual current equivalent test technology, many limitations of traditional test equipment are solved, system integration and automated testing are facilitated, and test costs are reduced.

[0097] It should be emphasized that the embodiments described in the present invention are illustrative rather than restrictive. Therefore, the present invention includes but is not limited to the embodiments described in the specific implementation manner. Any other implementation manners derived by those skilled in the art based on the technical solution of the present invention also fall within the scope of protection of the present invention.

Claims

1. A low voltage photovoltaic grid-connected circuit breaker detection method, characterized in that: The following steps are involved: Step 1: Based on the large-range power linear amplification technology with common current conduction but not common return, the circuit breaker operating environment is truly reproduced; Step 1.

1. Select a power amplifier to ensure that the range and accuracy of its output voltage and current meet the test requirements; Step 1.2, program and calibrate the power amplifier to set the appropriate output current waveform and amplitude; Step 1.3: Prepare the copper rod and make sure it has good conductivity and can withstand the current and voltage in the test; Step 1.4, the power amplifier synchronously injects currents of different loops into the copper rod according to preset parameters; Step 1.5, equip a data acquisition system to monitor and record the current and voltage waveforms and the response of the device under test in real time; Step 1.6: Process and analyze the real-time monitoring data; Step 2: Using the measurement data simulation technology based on the deviation model, the high-precision output of voltage and current during the test is ensured through the two-level correction method of software and hardware; Step 3: Perform closed-loop automatic test of the residual current protection function through the residual current equivalent test technology.

2. A low-voltage photovoltaic grid-connected circuit breaker detection method according to claim 1, characterized in that: The specific implementation method of step 1.6 is: extracting parameters from real-time monitoring and recording of current and voltage waveforms and responses of the device under test, analyzing the performance of the device under test under different working conditions, and evaluating tolerance, response speed and stability; Based on the analysis results, improvement suggestions or optimization plans are put forward to improve the performance of the equipment under test or the accuracy of the test method. The tolerance is improved by optimizing the insulating material, the response speed is improved by conducting FSM breaking principle analysis and step-by-step breaking method, and the stability is optimized by adjusting the electrodes and gaps to change the internal structure.

3. A low-voltage photovoltaic grid-connected circuit breaker detection method according to claim 1, characterized in that: The hardware correction method in step 2 is: correction based on a fast-response zero-static-error feedback hardware loop, and the software correction method is: software correction based on a measurement data simulation technology of a deviation model.

4. A low-voltage photovoltaic grid-connected circuit breaker detection method according to claim 3, characterized in that: The specific implementation method for correcting the fast-response zero-static-error feedback hardware loop is as follows: according to the detection result of the fast-response zero-static-error feedback hardware loop, the proportional gain parameter is adjusted to optimize the control performance; according to the steady-state output under different conditions, the effect of the zero-static-error feedback is verified; according to the performance test of the hardware loop under different working conditions, the performance indicators of the fast response and the zero-static-error feedback are verified to be up to standard.

5. A low-voltage photovoltaic grid-connected circuit breaker detection method according to claim 3, characterized in that: The specific implementation method of the software correction using the measurement data simulation technology based on the deviation model is as follows: constructing a deviation model, designing model parameters, and performing model training; predicting the measurement data through the deviation model, and comparing it with the actual measurement value, calculating the deviation amount, and identifying the source and type of the deviation; adjusting the model parameters to reduce the deviation based on the deviation analysis results, and integrating the correction algorithm in the software, receiving real-time measurement data, and calculating the correction value based on the deviation model.

6. A low-voltage photovoltaic grid-connected circuit breaker detection method according to claim 1, characterized in that: The specific implementation method of step 3 is: using a high-precision power source device to generate an analog signal that is identical to the residual current waveform that appears in an actual low-voltage photovoltaic grid-connected system, and recording the data; analyzing whether the behavior of the circuit breaker during the test meets the standard requirements based on the recorded data; and evaluating the performance of the circuit breaker in residual current protection to see whether it meets the requirements of relevant standards and specifications.

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