Method and system for frequency differential measurement of new energy system

Abstract

The invention discloses a method and a system for frequency differential measurement of a new energy system, and belongs to the technical field of power system measurement. The method comprises the following steps: carrying out PWU data acquisition on a new energy system, and preprocessing the acquired data to obtain a voltage signal; carrying out Hilbert conversion on the voltage signal to obtain an analysis signal; carrying out instantaneous phase unwrapping processing and frequency calculation on the analysis signal to obtain a frequency deviation; and performing frequency differential calculation based on the frequency deviation, and performing filtering smoothing processing on a calculation result of the frequency differential calculation to obtain a measurement result of frequency differential of the new energy system. According to the invention, rapid and accurate measurement of the frequency differential of the new energy system is realized, and the defects of a traditional PMU measurement method are overcome.

Description

Technical Field

[0001] The present invention relates to the technical field of power system measurement, and more specifically, to a method and system for frequency differential measurement of a new energy system. Background Art

[0002] With the deepening of the global energy revolution and low-carbon development, new energy represented by wind power and solar energy has been rapidly developed and widely used. However, new energy power generation has the characteristics of intermittency, volatility, uncertainty, etc., and its large-scale access has brought severe challenges to the frequency stability of the power system. In order to ensure the safe and stable operation of the power system, it is necessary to accurately evaluate the frequency characteristics and inertia level of the new energy system, which requires real-time and accurate measurement of the system frequency and its rate of change, that is, frequency differential.

[0003] Traditional power system frequency measurement mainly adopts the following methods:

[0004] Zero-crossing detection method: By detecting the zero-crossing point of the voltage or current signal, the time interval between adjacent zero-crossing points is calculated to obtain the frequency. This method is simple in principle and easy to implement, but the measurement accuracy and dynamic response are poor, and it is difficult to meet the requirements of new energy systems.

[0005] Fourier transform method: By performing Fourier transform on the sampled data, the frequency of the fundamental component is extracted in the frequency domain. This method has a high frequency resolution, but the amount of calculation is large, the real-time performance is poor, and the measurement results are easily affected by harmonics, interharmonics, etc.

[0006] Least squares fitting method: By fitting the sampled data with the least squares curve, the parameters of the voltage or current signal are estimated, and then the frequency is calculated. This method can suppress noise and harmonic interference to a certain extent, but the dynamic characteristics are poor and the real-time performance is insufficient.

[0007] Kalman filter method: By constructing a state space model of the voltage or current signal, the Kalman filter algorithm is used to estimate the frequency in real time. This method can track frequency changes online and has good dynamic characteristics, but the algorithm is highly complex and difficult to implement in engineering.

[0008] Phasor Measurement Unit (PMU): By synchronously sampling the voltage and current signals, the phasor value is calculated, and the frequency is estimated by the rate of change of the phasor value. PMU has the advantages of high precision and high real-time performance, but the frequency measurement of traditional PMU is still based on methods such as Fourier transform, and the calculation of frequency differential usually adopts numerical methods such as finite difference, which introduces large approximation errors and numerical oscillations.

[0009] The above traditional methods have the following limitations when measuring the frequency differential of new energy systems:

[0010] Insufficient measurement accuracy: The frequency of new energy systems changes rapidly and fluctuates greatly. Traditional methods are difficult to meet the requirements of high-precision measurements, and the measurement error can reach more than 0.1Hz / s.

[0011] Slow dynamic response: The dynamic change time of the frequency of new energy systems is often less than 100ms. The measurement delay of traditional methods is large, making it difficult to track rapid changes.

[0012] Poor anti-interference ability: There are a large number of power electronic devices in the new energy system, which generate abundant harmonics and interharmonics. Traditional methods are easily interfered by them and have poor measurement reliability.

[0013] Large numerical errors: The calculation of frequency differentials usually adopts numerical methods such as finite differences, which introduces large approximation errors and numerical oscillations, affecting the measurement accuracy and stability.

[0014] Lack of real-time performance: Traditional methods have large data processing and transmission delays, which makes it difficult to meet the needs of real-time monitoring and control of new energy systems. Summary of the invention

[0015] In view of the above problems, the present invention proposes a method for frequency differential measurement of a new energy system, comprising:

[0016] Collect PWU data for new energy systems and pre-process the collected data to obtain voltage signals;

[0017] Performing Hilbert transformation on the voltage signal to obtain an analytical signal;

[0018] Performing instantaneous phase unwrapping processing and frequency calculation on the analytical signal to obtain a frequency deviation;

[0019] Based on the frequency deviation, a frequency differential calculation is performed, and a calculation result of the frequency differential calculation is filtered and smoothed to obtain a measurement result of the frequency differential of the new energy system.

[0020] Optionally, PWU data collection for new energy systems includes:

[0021] For new energy systems, voltage signals are collected through PMU;

[0022] The sampling frequency of the voltage signal is not less than 10 kHz, and the sampling accuracy is higher than 0.1%.

[0023] Optionally, the collected data is preprocessed, including: removing DC, removing trends and filtering the collected data in sequence.

[0024] Optionally, performing Hilbert transform on the voltage signal to obtain an analytical signal includes:

[0025] An analytic signal in the complex domain is constructed by applying an imaginary signal with a 90° phase shift to the voltage signal.

[0026] Optionally, the real part of the analytical signal is the original signal, the imaginary part is the Hilbert transform of the original signal, the amplitude is the envelope of the original signal, and the phase is the instantaneous phase of the original signal.

[0027] Optionally, Hilbert transform, including: FFT fast Fourier transform and IFFT inverse fast Fourier transform.

[0028] Optionally, performing instantaneous phase unwrapping processing and frequency calculation on the analytical signal to obtain a frequency deviation includes:

[0029] Phase unwrapping processing is performed by judging whether the phase difference between two adjacent points of the analytical signal exceeds 180°, and if so, performing 2π phase compensation on the analytical signal;

[0030] The instantaneous phase after phase unwrapping is subjected to first-order numerical derivative calculation to obtain the instantaneous frequency;

[0031] The instantaneous frequency is compared with the nominal frequency to obtain a frequency deviation.

[0032] Optionally, first-order numerical derivatives are calculated using backward difference or central difference methods.

[0033] Optionally, based on the frequency deviation, a frequency differential calculation is performed, and a calculation result of the frequency differential calculation is filtered and smoothed, including:

[0034] Performing a first-order numerical derivative calculation on the frequency deviation to obtain a frequency differential;

[0035] The calculated frequency differential is filtered and smoothed to remove high-frequency noise and numerical oscillation.

[0036] Optionally, filtering and smoothing are performed using moving average, exponential smoothing or Kalman filtering methods.

[0037] In another aspect, the present invention further provides a system for frequency differential measurement of a new energy system, comprising:

[0038] A data acquisition unit, used for collecting PWU data for the new energy system and preprocessing the collected data to obtain a voltage signal;

[0039] A transformation and analysis unit, used for performing Hilbert transformation on the voltage signal to obtain an analysis signal;

[0040] A calculation unit, used for performing instantaneous phase unwrapping processing and frequency calculation on the analytical signal to obtain a frequency deviation;

[0041] The measuring unit is used to perform frequency differential calculation based on the frequency deviation, and filter and smooth the calculation result of the frequency differential calculation to obtain the measurement result of the frequency differential of the new energy system.

[0042] Optionally, PWU data collection for new energy systems includes:

[0043] For new energy systems, voltage signals are collected through PMU;

[0044] The sampling frequency of the voltage signal is not less than 10 kHz, and the sampling accuracy is higher than 0.1%.

[0045] Optionally, the collected data is preprocessed, including: removing DC, removing trends and filtering the collected data in sequence.

[0046] Optionally, performing Hilbert transform on the voltage signal to obtain an analytical signal includes:

[0047] An analytic signal in the complex domain is constructed by applying an imaginary signal with a 90° phase shift to the voltage signal.

[0048] Optionally, the real part of the analytical signal is the original signal, the imaginary part is the Hilbert transform of the original signal, the amplitude is the envelope of the original signal, and the phase is the instantaneous phase of the original signal.

[0049] Optionally, Hilbert transform, including: FFT fast Fourier transform and IFFT inverse fast Fourier transform.

[0050] Optionally, performing instantaneous phase unwrapping processing and frequency calculation on the analytical signal to obtain a frequency deviation includes:

[0051] Phase unwrapping processing is performed by judging whether the phase difference between two adjacent points of the analytical signal exceeds 180°, and if so, performing 2π phase compensation on the analytical signal;

[0052] The instantaneous phase after phase unwrapping is subjected to first-order numerical derivative calculation to obtain the instantaneous frequency;

[0053] The instantaneous frequency is compared with the nominal frequency to obtain a frequency deviation.

[0054] Optionally, first-order numerical derivatives are calculated using backward difference or central difference methods.

[0055] Optionally, based on the frequency deviation, a frequency differential calculation is performed, and a calculation result of the frequency differential calculation is filtered and smoothed, including:

[0056] Performing a first-order numerical derivative calculation on the frequency deviation to obtain a frequency differential;

[0057] The calculated frequency differential is filtered and smoothed to remove high-frequency noise and numerical oscillation.

[0058] Optionally, filtering and smoothing are performed using moving average, exponential smoothing or Kalman filtering methods.

[0059] In yet another aspect, the present invention further provides a computing device, comprising: one or more processors;

[0060] a processor for executing one or more programs;

[0061] When the one or more programs are executed by the one or more processors, the above-described method is implemented.

[0062] In yet another aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed, the method described above is implemented.

[0063] Compared with the prior art, the present invention has the following beneficial effects:

[0064] The present invention provides a method for frequency differential measurement of a new energy system, comprising: performing PWU data acquisition for the new energy system, and preprocessing the acquired data to obtain a voltage signal; performing Hilbert transform on the voltage signal to obtain an analytical signal; performing instantaneous phase unwrapping processing and frequency calculation on the analytical signal to obtain a frequency deviation; performing frequency differential calculation based on the frequency deviation, and filtering and smoothing the calculation result of the frequency differential calculation to obtain a measurement result of the frequency differential of the new energy system. The present invention realizes fast and accurate measurement of the frequency differential of the new energy system, and overcomes the shortcomings of the traditional PMU measurement method. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 is a flow chart of the method of the present invention;

[0066] Figure 2 It is a schematic diagram of an embodiment of the method of the present invention;

[0067] Figure 3 A flowchart of an embodiment of the method of the present invention;

[0068] Figure 4 It is a structural diagram of the system of the present invention. DETAILED DESCRIPTION

[0069] Now, exemplary embodiments of the present invention are described with reference to the accompanying drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. These embodiments are provided to disclose the present invention in detail and completely and to fully convey the scope of the present invention to those skilled in the art. The terms used in the exemplary embodiments shown in the accompanying drawings are not intended to limit the present invention. In the accompanying drawings, the same units / elements are marked with the same reference numerals.

[0070] Unless otherwise specified, the terms (including technical terms) used herein have the commonly understood meanings to those skilled in the art. In addition, it is understood that the terms defined in commonly used dictionaries should be understood to have the same meanings as those in the context of the relevant fields, and should not be understood as idealized or overly formal meanings.

[0071] Embodiment 1:

[0072] The present invention proposes a method for frequency differential measurement of a new energy system, such as Figure 1 As shown, including:

[0073] Step 1: Collect PWU data for the new energy system and pre-process the collected data to obtain a voltage signal;

[0074] Step 2: Perform Hilbert transform on the voltage signal to obtain an analytical signal;

[0075] Step 3, performing instantaneous phase unwrapping processing and frequency calculation on the analytical signal to obtain a frequency deviation;

[0076] Step 4: Based on the frequency deviation, perform frequency differential calculation, and filter and smooth the calculation result of the frequency differential calculation to obtain the measurement result of the frequency differential of the new energy system.

[0077] Among them, PWU data collection for new energy systems includes:

[0078] For new energy systems, voltage signals are collected through PMU;

[0079] The sampling frequency of the voltage signal is not less than 10 kHz, and the sampling accuracy is higher than 0.1%.

[0080] The collected data is preprocessed, including: removing direct current, removing trends and filtering the collected data in sequence.

[0081] The voltage signal is subjected to Hilbert transformation to obtain an analytical signal, including:

[0082] An analytic signal in the complex domain is constructed by applying an imaginary signal with a 90° phase shift to the voltage signal.

[0083] Among them, the real part of the analytical signal is the original signal, the imaginary part is the Hilbert transform of the original signal, the amplitude is the envelope of the original signal, and the phase is the instantaneous phase of the original signal.

[0084] Among them, Hilbert transform includes: FFT fast Fourier transform and IFFT inverse fast Fourier transform.

[0085] The instantaneous phase unwrapping processing and frequency calculation are performed on the analytical signal to obtain the frequency deviation, including:

[0086] Phase unwrapping processing is performed by judging whether the phase difference between two adjacent points of the analytical signal exceeds 180°, and if so, performing 2π phase compensation on the analytical signal;

[0087] The instantaneous phase after phase unwrapping is subjected to first-order numerical derivative calculation to obtain the instantaneous frequency;

[0088] The instantaneous frequency is compared with the nominal frequency to obtain a frequency deviation.

[0089] Among them, the first-order numerical derivative calculation is performed using the backward difference method or the central difference method.

[0090] Wherein, based on the frequency deviation, frequency differential calculation is performed, and filtering and smoothing processing is performed on the calculation result of the frequency differential calculation, including:

[0091] Performing a first-order numerical derivative calculation on the frequency deviation to obtain a frequency differential;

[0092] The calculated frequency differential is filtered and smoothed to remove high-frequency noise and numerical oscillation.

[0093] Among them, the filtering and smoothing processing adopts moving average, exponential smoothing or Kalman filtering method for processing.

[0094] Combine the following Figure 2 , Figure 3 And implementation cases are provided to further illustrate the present invention;

[0095] The process of implementing the case includes:

[0096] 1.PMU data acquisition and preprocessing;

[0097] PMU collects voltage signals with a sampling frequency no less than 10kHz and a sampling accuracy better than 0.1%;

[0098] Pre-process the collected voltage signal, including DC removal, trend removal, filtering, etc., to improve the quality and stability of the signal;

[0099] The preprocessed voltage signal is transmitted to the measurement module in real time, and the transmission delay does not exceed 10ms.

[0100] 2. Analytical signal calculation based on Hilbert transform;

[0101] Perform Hilbert transform on the preprocessed voltage signal to obtain its analytical signal;

[0102] The Hilbert transform constructs an analytical signal in the complex domain by applying a 90° phase-shifted imaginary signal to the original signal;

[0103] The real part of the analytical signal is the original signal, the imaginary part is the Hilbert transform of the original signal, the amplitude is the envelope of the original signal, and the phase is the instantaneous phase of the original signal;

[0104] The Hilbert transform can be efficiently implemented through FFT (Fast Fourier Transform) and IFFT (Inverse Fast Fourier Transform), with a computational delay of no more than 5ms.

[0105] 3. Instantaneous phase unwrapping and frequency calculation;

[0106] Unwrap the instantaneous phase of the analytical signal to eliminate phase jumps and obtain a continuous phase trajectory;

[0107] Phase unwrapping is achieved by judging whether the phase difference between two adjacent points exceeds 180°. If so, a 2π phase compensation is performed.

[0108] Taking the first-order numerical derivative of the instantaneous phase after unwrapping, the instantaneous frequency is obtained;

[0109] The first-order numerical derivative can adopt methods such as backward difference and central difference, which can be selected according to the real-time and accuracy requirements, and the calculation delay should not exceed 1ms;

[0110] The calculated instantaneous frequency is compared with the nominal frequency (eg, 50 Hz) to obtain the frequency deviation.

[0111] 4. Frequency differential calculation and filtering smoothing;

[0112] Take the first-order numerical derivative of the instantaneous frequency to obtain the frequency differential;

[0113] The first-order numerical derivative can be calculated using the same differential method as the frequency calculation, and the calculation delay does not exceed 1ms;

[0114] The calculated frequency differential is filtered and smoothed to remove high-frequency noise and numerical oscillation;

[0115] Filter smoothing can use moving average, exponential smoothing, Kalman filtering and other methods, which are selected according to noise characteristics and response speed, and the processing delay does not exceed 5ms;

[0116] The frequency differential after filtering and smoothing is used as the final measurement result for subsequent application and analysis.

[0117] The implementation steps of the present invention also include reporting of subsequent results, and evaluation and calibration of the method of the present invention, including the following:

[0118] 5. Report and apply measurement results;

[0119] The frequency differential measurement results are packaged and reported together with other PMU measurement quantities (such as voltage amplitude, phase angle, frequency, etc.);

[0120] The reporting period is configured according to application requirements and is generally no more than 100ms;

[0121] The measurement results are transmitted through standardized data interfaces (such as IEEE C37.118) to ensure data interoperability and compatibility;

[0122] The measurement results can be used in application scenarios such as inertia estimation, stability assessment, and control optimization of new energy systems, supporting the safe and stable operation and optimized scheduling of new energy.

[0123] 6. Measurement performance evaluation and calibration;

[0124] Conduct a comprehensive performance evaluation of the frequency differential measurement method, including indicators such as accuracy, speed, stability, and reliability;

[0125] The accuracy evaluation is achieved by comparing with a high-precision frequency reference source. The evaluation indicators include absolute error, relative error, root mean square error, etc.

[0126] Speed ​​evaluation is achieved by measuring the end-to-end delay of data. Evaluation indicators include acquisition delay, transmission delay, calculation delay, reporting delay, etc.

[0127] Stability assessment is achieved through long-term continuous operation, and the assessment indicators include the fluctuation range of measurement results, drift trends, abnormal events, etc.

[0128] Through the organic combination of the above steps and technical links, the present invention realizes the fast and accurate measurement of the frequency differential of the new energy system, overcomes the shortcomings of the traditional PMU measurement method, and provides key technical support for the stability analysis and optimization control of the new energy system.

[0129] Compared with the prior art, the present invention has the following significant advantages and innovative effects:

[0130] (1) Significantly improved frequency differential measurement accuracy;

[0131] By adopting high-precision synchronous phasor measurement technology, improving sampling rate and quantization accuracy, and combining the direct calculation method of frequency differential, the present invention controls the frequency differential measurement error within 0.01 Hz / s, which is more than one order of magnitude higher than the traditional method. It meets the stringent requirements of new energy system stability analysis on frequency differential measurement accuracy and lays a data foundation for refined modeling, stability analysis and optimization control of new energy systems.

[0132] (2) Greatly shortened the frequency differential measurement delay;

[0133] By optimizing synchronous sampling, data transmission, and frequency differential calculations, and reducing unnecessary data processing and communication overhead, the present invention controls the end-to-end delay of frequency differential measurement to within 50ms, which is more than 80% shorter than traditional methods. It achieves real-time tracking and response to rapid changes in the frequency of new energy systems, greatly improving the dynamic characteristics and control performance of new energy systems.

[0134] (3) Effectively improve the anti-interference ability of frequency differential measurement;

[0135] The analytical signal method is introduced, and the envelope signal is constructed using Hilbert transform, which effectively suppresses the influence of power quality problems on frequency differential measurement. Compared with the traditional method, the frequency differential measurement results of the present invention show stronger robustness and consistency in harmonic and noise environments, and the measurement reliability is improved by more than 50%, ensuring the effectiveness and availability of the measurement results under complex working conditions.

[0136] (4) Significantly reduced the numerical error of frequency differential calculation;

[0137] The frequency differential is directly calculated using the phase information of the analytical signal, avoiding the truncation error and rounding error introduced by the traditional differential operation. Compared with the numerical difference method, the calculation error of the present invention is reduced by more than 90%, and the numerical stability and dynamic performance are significantly improved, providing high-quality data input for subsequent stability analysis and control optimization.

[0138] (5) The engineering application of frequency differential measurement method was realized;

[0139] Through software and hardware optimization design, full use of the existing PMU platform computing and communication resources, and the use of modular and parameterized design ideas, the seamless integration of the frequency differential measurement algorithm and the PMU platform is achieved. The present invention has strong engineering applicability and operability, is easy to promote and apply in actual systems, and provides a complete set of frequency differential measurement solutions for engineering and technical personnel.

[0140] (6) Provides key support for stability analysis and control of new energy systems;

[0141] The high-precision and high-real-time frequency differential measurement results provide reliable data support for key tasks such as inertia estimation, stability margin assessment, and primary frequency modulation control of new energy systems. By reflecting the trend of system inertia changes through frequency differential, assessing the frequency stability margin, and guiding the setting of primary frequency modulation parameters, the present invention promotes the adaptive optimization control of new energy systems and improves the absorption ratio of new energy and the reliability of power supply.

[0142] In summary, the new energy system frequency differential fast measurement method proposed in the present invention has achieved significant improvements and innovative breakthroughs in measurement accuracy, real-time performance, reliability, numerical stability, etc., and has provided a solid theoretical basis and technical support for the stability analysis and optimization control of the new energy system.

[0143] The following is an explanation based on specific cases.

[0144] like Figure 2 and 3 As shown in the overall frame Figure 2 The application architecture of the present invention in the new energy system is shown, which mainly includes:

[0145] New energy systems: wind farms, photovoltaic power stations, microgrids, etc.

[0146] Frequency differential fast measurement device cluster: multiple PMU measurement units deployed at each new energy site.

[0147] Data aggregation unit: aggregates the frequency differential measurement data of each PMU and performs data alignment and quality assessment.

[0148] Stability analysis unit: Based on frequency differential data, it evaluates the frequency stability margin of the new energy system and guides primary frequency regulation control.

[0149] Energy management system: optimize new energy output scheduling and energy storage configuration, and improve new energy consumption capacity and economy.

[0150] Fast measurement flow in frequency differentiation Figure 3 The core measurement algorithm flow of the present invention is shown in FIG. 1 , and the main steps include:

[0151] PMU sampling voltage signal

[0152] Analyze signal transformation and extract voltage positive sequence component

[0153] Unwind the phase of the voltage positive sequence component to eliminate phase jumps

[0154] Derivative the unwrapped phase signal to obtain the frequency signal

[0155] Derivative the frequency signal to obtain the frequency differential signal

[0156] Filter the frequency differential signal to remove high-frequency noise and numerical oscillation

[0157] Pack the frequency differential measurement results and add a timestamp

[0158] Send the frequency differential data packet to the data aggregation unit for subsequent stability analysis and control command generation

[0159] The above block diagrams and flow charts intuitively demonstrate the overall application architecture and core measurement algorithm of the present invention, embodying the innovative principle and implementation path of fast frequency differential measurement based on synchronous measurement and analytical signal method, and providing clear technical guidance and reference for readers to understand and implement this patent.

[0160] Taking an offshore wind farm as an example, the present invention is verified, including:

[0161] An offshore wind farm consists of 100 wind turbines with a single unit capacity of 5MW, with a total installed capacity of 500MW, which is connected to the grid through submarine cables. In order to achieve frequency stability management and primary frequency regulation control of the wind farm, it is necessary to perform high-precision, high-real-time synchronous measurement of the frequency and frequency differential of each wind turbine.

[0162] (1) A PMU-based edge measurement device is installed in the cabin control cabinet of each wind turbine. The device uses a high-precision A / D sampling module, FPGA parallel computing module, and multi-core CPU processing module to achieve synchronous sampling up to 10kHz and millisecond-level frequency differentiation resolution.

[0163] (2) The edge measurement device of each wind turbine achieves precise timing through its own GPS receiver and realizes time synchronization within the station through the optical fiber ring network. The clock synchronization accuracy is better than 1μs.

[0164] (3) The edge measurement device synchronously samples the three-phase voltage signals of the wind turbine at a frequency of 10 kHz, and calculates the analytical signal and envelope signal of the voltage positive sequence component in real time.

[0165] (4) The edge measurement device calculates the frequency and frequency differential in real time by phase unwrapping and derivative calculation of the voltage positive sequence component. The frequency measurement range is 45-55Hz, with a measurement accuracy better than 0.001Hz; the frequency differential measurement range is -5~5Hz / s, with a measurement accuracy better than 0.005Hz / s.

[0166] (5) The edge measurement device sends frequency and frequency differential data to the data aggregation unit of the wind farm monitoring center every 10 ms, and the transmission delay is less than 2 ms.

[0167] (6) The data aggregation unit receives the frequency and frequency differential data streams from all edge measurement devices, and performs time alignment, anomaly identification, and data quality assessment to generate a wind farm-level synchronized frequency and frequency differential measurement data set.

[0168] (7) The stability analysis application unit of the monitoring center obtains the synchronous measurement data from the data aggregation unit, combines it with the real-time operating conditions of the wind farm, evaluates the frequency stability margin of the wind farm, calculates the primary frequency regulation power command, and implements coordinated frequency regulation control of each wind turbine by issuing control commands.

[0169] (8) The wind farm’s energy management system obtains margin assessment results and frequency regulation capacity requirements from stability analysis applications, optimizes the wind farm’s active power scheduling and energy storage configuration, and ensures the wind farm’s safe, economical, and efficient operation.

[0170] Through field tests and long-term operation statistics, this embodiment has achieved remarkable results:

[0171] (1) The frequency differential measurement accuracy reaches 0.005 Hz / s, which is more than double that of conventional methods, providing high-quality data support for primary frequency control of wind farms.

[0172] (2) The frequency differential measurement delay is less than 20ms, which meets the control requirements of the wind farm's fast frequency response and effectively suppresses the frequency fluctuation and power shock when the wind farm is connected to the grid.

[0173] (3) Actual measurement statistics show that the reliability of the frequency differential measurement device reaches 99.95%. It can operate stably under complex sea conditions and severe weather, and the operation and maintenance costs are greatly reduced.

[0174] (4) The frequency stability margin assessment results of wind farms based on frequency differential are highly consistent with the actual operation, with a relative error of less than 5%, providing a reliable basis for the safe and stable control of wind farms.

[0175] (5) By using frequency differential to guide the primary frequency regulation control of the wind farm, the primary frequency regulation response time of the wind farm is shortened by 50%, the frequency regulation accuracy is improved by 30%, and the grid-connected performance is significantly improved.

[0176] (6) Combined with the optimized configuration and real-time dispatch of the energy storage system, the peak-shaving and valley-filling capacity of the wind farm has increased by 20%, the proportion of wind power curtailment and power rationing has decreased by 10%, and the economic and environmental benefits have been significantly improved.

[0177] This example fully demonstrates the engineering application value and practical effect of the frequency differential fast measurement method in offshore wind farms. Through accurate, real-time and reliable frequency differential measurement, it provides strong data support and technical guarantee for key tasks such as frequency stability analysis, primary frequency control, and energy storage optimization configuration of wind farms.

[0178] Embodiment 2:

[0179] The present invention also proposes a system 200 for frequency differential measurement of a new energy system, such as Figure 4 As shown, including:

[0180] The data acquisition unit 201 is used to collect PWU data for the new energy system and pre-process the collected data to obtain a voltage signal;

[0181] A transformation and analysis unit 202, configured to perform Hilbert transformation on the voltage signal to obtain an analysis signal;

[0182] The calculation unit 203 is used to perform instantaneous phase unwrapping processing and frequency calculation on the analytical signal to obtain a frequency deviation;

[0183] The measuring unit 204 is used to perform frequency differential calculation based on the frequency deviation, and perform filtering and smoothing processing on the calculation result of the frequency differential calculation to obtain the measurement result of the frequency differential of the new energy system.

[0184] Among them, PWU data collection for new energy systems includes:

[0185] For new energy systems, voltage signals are collected through PMU;

[0186] The sampling frequency of the voltage signal is not less than 10 kHz, and the sampling accuracy is higher than 0.1%.

[0187] The collected data is preprocessed, including: removing direct current, removing trends and filtering the collected data in sequence.

[0188] The voltage signal is subjected to Hilbert transformation to obtain an analytical signal, including:

[0189] An analytic signal in the complex domain is constructed by applying an imaginary signal with a 90° phase shift to the voltage signal.

[0190] Among them, the real part of the analytical signal is the original signal, the imaginary part is the Hilbert transform of the original signal, the amplitude is the envelope of the original signal, and the phase is the instantaneous phase of the original signal.

[0191] Among them, Hilbert transform includes: FFT fast Fourier transform and IFFT inverse fast Fourier transform.

[0192] The instantaneous phase unwrapping processing and frequency calculation are performed on the analytical signal to obtain the frequency deviation, including:

[0193] Phase unwrapping processing is performed by judging whether the phase difference between two adjacent points of the analytical signal exceeds 180°, and if so, performing 2π phase compensation on the analytical signal;

[0194] The instantaneous phase after phase unwrapping is subjected to first-order numerical derivative calculation to obtain the instantaneous frequency;

[0195] The instantaneous frequency is compared with the nominal frequency to obtain a frequency deviation.

[0196] Among them, the first-order numerical derivative calculation is performed using the backward difference method or the central difference method.

[0197] Wherein, based on the frequency deviation, frequency differential calculation is performed, and filtering and smoothing processing is performed on the calculation result of the frequency differential calculation, including:

[0198] Performing a first-order numerical derivative calculation on the frequency deviation to obtain a frequency differential;

[0199] The calculated frequency differential is filtered and smoothed to remove high-frequency noise and numerical oscillation.

[0200] Among them, the filtering and smoothing processing adopts moving average, exponential smoothing or Kalman filtering method for processing.

[0201] The present invention realizes fast and accurate measurement of frequency differential of new energy system, and overcomes the shortcomings of traditional PMU measurement method.

[0202] Embodiment 3:

[0203] Based on the same inventive concept, the present invention also provides a computer device, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding functions, so as to implement the steps of the method in the above embodiment.

[0204] Embodiment 4:

[0205] Based on the same inventive concept, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device for storing programs and data. It is understandable that the computer-readable storage medium here can include both a built-in storage medium in a computer device and an extended storage medium supported by the computer device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by a processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of the method in the above embodiment.

[0206] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The schemes in the embodiments of the present invention may be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0207] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0208] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0209] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0210] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0211] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for frequency differential measurement of a new energy system, characterized in that: include: Collect PWU data for new energy systems and pre-process the collected data to obtain voltage signals; Performing Hilbert transformation on the voltage signal to obtain an analytical signal; Performing instantaneous phase unwrapping processing and frequency calculation on the analytical signal to obtain a frequency deviation; Based on the frequency deviation, a frequency differential calculation is performed, and a calculation result of the frequency differential calculation is filtered and smoothed to obtain a measurement result of the frequency differential of the new energy system.

2. The method according to claim 1, characterized in that The PWU data collection for the new energy system includes: For new energy systems, voltage signals are collected through PMU; The sampling frequency of the voltage signal is not less than 10 kHz, and the sampling accuracy is higher than 0.1%.

3. The method according to claim 1, characterized in that The preprocessing of the collected data includes: performing DC removal, trend removal and filtering processing on the collected data in sequence.

4. The method according to claim 1, characterized in that The step of performing Hilbert transformation on the voltage signal to obtain an analytical signal includes: An analytic signal in the complex domain is constructed by applying an imaginary signal with a 90° phase shift to the voltage signal.

5. The method according to claim 4, characterized in that The real part of the analytical signal is the original signal, the imaginary part is the Hilbert transform of the original signal, the amplitude is the envelope of the original signal, and the phase is the instantaneous phase of the original signal.

6. The method according to claim 4, characterized in that The Hilbert transform includes: FFT fast Fourier transform and IFFT inverse fast Fourier transform.

7. The method according to claim 1, characterized in that The performing instantaneous phase unwrapping processing and frequency calculation on the analytical signal to obtain the frequency deviation includes: Phase unwrapping processing is performed by judging whether the phase difference between two adjacent points of the analytical signal exceeds 180°, and if so, performing 2π phase compensation on the analytical signal; The instantaneous phase after phase unwrapping is subjected to first-order numerical derivative calculation to obtain the instantaneous frequency; The instantaneous frequency is compared with the nominal frequency to obtain a frequency deviation.

8. The method according to claim 7, characterized in that The first-order numerical derivative is calculated by using a backward difference method or a central difference method.

9. The method according to claim 1, characterized in that: The step of performing frequency differential calculation based on the frequency deviation and filtering and smoothing the calculation result of the frequency differential calculation comprises: Performing a first-order numerical derivative calculation on the frequency deviation to obtain a frequency differential; The calculated frequency differential is filtered and smoothed to remove high-frequency noise and numerical oscillation.

10. The method according to claim 9, characterized in that The filtering and smoothing process is performed by using a moving average, exponential smoothing or Kalman filtering method.

11. A system for frequency differential measurement of a new energy system, characterized in that: include: A data acquisition unit, used for collecting PWU data for the new energy system and preprocessing the collected data to obtain a voltage signal; A transformation and analysis unit, used for performing Hilbert transformation on the voltage signal to obtain an analysis signal; A calculation unit, used for performing instantaneous phase unwrapping processing and frequency calculation on the analytical signal to obtain a frequency deviation; The measuring unit is used to perform frequency differential calculation based on the frequency deviation, and filter and smooth the calculation result of the frequency differential calculation to obtain the measurement result of the frequency differential of the new energy system.

12. The system according to claim 11, characterized in that The PWU data collection for the new energy system includes: For new energy systems, voltage signals are collected through PMU; The sampling frequency of the voltage signal is not less than 10 kHz, and the sampling accuracy is higher than 0.1%.

13. The system according to claim 11, characterized in that The preprocessing of the collected data includes: performing DC removal, trend removal and filtering processing on the collected data in sequence.

14. The system according to claim 11, characterized in that The step of performing Hilbert transformation on the voltage signal to obtain an analytical signal includes: An analytic signal in the complex domain is constructed by applying an imaginary signal with a 90° phase shift to the voltage signal.

15. The system according to claim 14, characterized in that The real part of the analytical signal is the original signal, the imaginary part is the Hilbert transform of the original signal, the amplitude is the envelope of the original signal, and the phase is the instantaneous phase of the original signal.

16. The system according to claim 14, characterized in that The Hilbert transform includes: FFT fast Fourier transform and IFFT inverse fast Fourier transform.

17. The system according to claim 11, characterized in that The performing instantaneous phase unwrapping processing and frequency calculation on the analytical signal to obtain the frequency deviation includes: Phase unwrapping processing is performed by judging whether the phase difference between two adjacent points of the analytical signal exceeds 180°, and if so, performing 2π phase compensation on the analytical signal; The instantaneous phase after phase unwrapping is subjected to first-order numerical derivative calculation to obtain the instantaneous frequency; The instantaneous frequency is compared with the nominal frequency to obtain a frequency deviation.

18. The system according to claim 17, characterized in that The first-order numerical derivative is calculated by using a backward difference method or a central difference method.

19. The system according to claim 11, characterized in that The step of performing frequency differential calculation based on the frequency deviation and filtering and smoothing the calculation result of the frequency differential calculation comprises: Performing a first-order numerical derivative calculation on the frequency deviation to obtain a frequency differential; The calculated frequency differential is filtered and smoothed to remove high-frequency noise and numerical oscillation.

20. The system according to claim 19, characterized in that The filtering and smoothing process is performed by using a moving average, exponential smoothing or Kalman filtering method.

21. A computer device, characterized in that: include: one or more processors; a processor for executing one or more programs; When the one or more programs are executed by the one or more processors, the method according to any one of claims 1 to 10 is implemented.

22. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed, the method according to any one of claims 1 to 10 is implemented.

Images