Wind-light-storage-same-site fast response combined regulation system

Abstract

The application relates to the technical field of power system automation, and particularly discloses a wind-solar-storage co-located fast response combined regulation system, which extracts standardized oscillation characteristic quantities through a real-time monitoring module; realizes characteristic quantity interaction of adjacent units and constructs a distributed oscillation characteristic set through a neighborhood communication module; uses a cluster decision module to reach cluster consensus based on a distributed consistency algorithm and generate a counterphase compensation current parameter; completes compensation parameter and local instruction fusion and drive signal generation through an adaptive injection module; and finally realizes adaptive adjustment of output intensity with the aid of a closed-loop optimization module; the application adopts a fully distributed architecture, replaces centralized control through local information interaction, avoids single-point failure risks, improves the suppression speed and precision of the system on wideband oscillation, and guarantees the safe and stable operation of the wind-solar-storage co-located system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power system automation, in particular to a wind-solar-storage co-located fast response joint regulation system. BACKGROUND

[0002] As an integrated development mode, the wind-solar-storage co-located system can effectively suppress the intermittency and volatility of renewable energy and improve the consumption capacity of green energy of the power grid. However, a large number of grid-connected power electronic converters in the system change the dynamic characteristics of the system, and there are complex interactions between the fast and multi-time scale control loops and the impedance of the traditional power grid, which can easily cause subsynchronous or supersynchronous oscillation problems. This kind of wideband oscillation has high frequency and fast propagation speed, and if it cannot be suppressed in time, it can cause overheat damage to transformers, capacitors and other devices within a few minutes, and even cause large-scale off-grid accidents, seriously threatening the safe and stable operation of the power grid.

[0003] The prior art has the following disadvantages:

[0004] In a joint power generation system containing wind power, photovoltaic and energy storage devices, when the equivalent impedance of the power grid changes due to the change of the topological structure caused by power grid faults, harmful interactions occur between control subsystems of different response time scales. Specifically, under certain grid impedance conditions, the microsecond-level current inner loop control of the wind turbine grid-connected inverter and the hundred-millisecond-level power regulation instruction of the energy storage system form a nonlinear coupling, thereby inducing subsupersynchronous oscillation of several hundred hertz. High-frequency oscillation will cause serious distortion of the voltage and current waveform at the grid-connected point, leading to overheat damage to transformers, capacitors and other devices in the power grid due to high-frequency harmonic current, and further causing large-scale off-grid accidents, seriously threatening the safe and stable operation of the regional power grid. Existing control strategies are difficult to coordinate control loops of different time constants and cannot effectively suppress such wideband oscillation problems. SUMMARY

[0005] The purpose of the present application is to provide a wind-solar-storage co-located fast response joint regulation system to solve the problems in the above background.

[0006] The purpose of the present application can be achieved by the following technical solutions:

[0007] The wind-solar-storage co-located fast response joint regulation system comprises:

[0008] A real-time monitoring module, the real-time monitoring module is used for collecting local electrical quantity data, and extracting frequency characteristics, amplitude characteristics and phase characteristics of abnormal oscillation through real-time frequency spectrum analysis to generate standardized oscillation characteristic quantities;

[0009] A neighborhood communication module is configured to interact with the grid-connected converter units within a predefined neighborhood range in a bidirectional manner of standardized oscillation characteristics, and receive the oscillation characteristics of the neighboring grid-connected converter units, and construct a distributed oscillation characteristic set;

[0010] A cluster decision module is configured to reach a cluster consensus on the dominant oscillation frequency based on the distributed oscillation characteristic set through a distributed consensus algorithm, and generate a corresponding anti-phase compensation current parameter;

[0011] An adaptive injection module is configured to fuse the anti-phase compensation current parameter with a local original current control instruction, generate a driving signal through pulse width modulation, and realize cooperative suppression of the dominant oscillation frequency.

[0012] A closed-loop optimization module is configured to continuously monitor the oscillation amplitude variation, and adjust the output intensity of the anti-phase compensation current parameter according to the monitoring result until the oscillation is completely eliminated.

[0013] As a further scheme of the present application, the acquisition process of the standardized oscillation characteristics comprises:

[0014] The grid-connected point voltage and current instantaneous values are continuously collected at a preset oversampling rate, and are recorded as original signals, the original signals are subjected to anti-aliasing filtering processing, the continuous signals are divided into data segments of a fixed length in an overlapping sliding window manner, and the adjacent data segments have an overlapping area with a preset proportion;

[0015] Each data segment is subjected to adaptive noise perfect set decomposition, the signal is decomposed into a plurality of intrinsic mode function components, and high-precision spectrum analysis is performed on each component to identify the abnormal oscillation frequency components contained therein and the corresponding amplitude and phase information;

[0016] The extracted oscillation frequency, amplitude and phase information are packaged into standardized oscillation characteristics in a preset format, the standardized oscillation characteristics include a time stamp, a device identifier and a confidence index; the confidence index is calculated by comprehensively considering the signal signal-to-noise ratio, the spectrum analysis convergence and the mode component stability;

[0017] The standardized oscillation characteristics are stored in a first-in-first-out queue, and the latest standardized oscillation characteristics are output at a fixed time interval.

[0018] As a further scheme of the present application, the process of the predefined neighborhood range comprises:

[0019] A physical neighborhood table is initialized based on the electrical wiring topology of the wind-solar-storage co-located system and the electrical distance between each grid-connected converter unit; during the operation of the wind-solar-storage co-located system, the transmission delay and the data packet loss rate of the communication link with each potential adjacent unit are monitored in real time; the comprehensive weight index of the electrical coupling strength and the communication quality is calculated, and the electrical coupling strength is represented by the voltage variation of the adjacent node caused by the unit current variation; the neighborhood range is updated, the grid-connected converter units with the comprehensive weight index higher than the preset threshold are determined as the effective adjacent units, and a stable communication connection is established.

[0020] As a further scheme of the present application, the distributed oscillation feature set is specifically constructed, and the construction specifically includes:

[0021] The standardized oscillation feature quantity is received, and a receiving time stamp and a source device identifier are attached to each standardized oscillation feature quantity; the time synchronization alignment processing is performed on all the standardized oscillation feature quantities based on the time stamp of the local oscillation feature quantity, so as to eliminate the timing error caused by the communication delay; the consistency verification and data fusion are performed on the multiple standardized oscillation feature quantities after the time alignment, the abnormal standardized oscillation feature quantity deviating from the cluster consensus is eliminated, and the remaining standardized oscillation feature quantities are weighted and averaged according to the confidence index, so as to generate a fusion feature quantity capable of representing the oscillation state of the local area; the local standardized oscillation feature quantity and the fusion feature quantity are jointly composed into the distributed oscillation feature set.

[0022] As a further scheme of the present application, the cluster consensus on the dominant oscillation frequency is achieved through the distributed consistency algorithm, and the cluster consensus specifically includes:

[0023] Based on the distributed oscillation feature set, each grid-connected converter unit first independently proposes a candidate value of the dominant oscillation frequency identified by the grid-connected converter unit; the candidate value and the confidence weight thereof are exchanged between each grid-connected converter unit and the adjacent grid-connected converter unit; through the weighted average consistency protocol of multiple rounds of iteration, the output values of all the units tend to be consistent; when the variance of the frequency values output by each grid-connected converter unit is less than a preset threshold, it is determined that the cluster consensus on the dominant oscillation frequency is achieved.

[0024] As a further scheme of the present application, the corresponding anti-phase compensation current parameter is generated, and the anti-phase compensation current parameter specifically includes:

[0025] According to the achieved cluster consensus frequency, the target frequency of the compensation current is determined; based on the oscillation amplitude information of the local and neighborhood in the distributed oscillation feature set, the initial amplitude parameter of the compensation current is calculated through a predefined amplitude-intensity mapping relationship; the phase parameter of the compensation current is generated by superimposing a phase shift of one hundred and eighty degrees based on the oscillation phase detected locally; the target frequency, the amplitude parameter and the phase parameter are jointly combined into the complete anti-phase compensation current parameter.

[0026] As a further scheme of the present application, the fusion of the anti-phase compensation current parameter with the local original current control instruction specifically comprises:

[0027] The anti-phase compensation current parameter is transformed from the rotating coordinate system to the stationary coordinate system to obtain three-phase instantaneous compensation current instructions; the obtained three-phase instantaneous compensation current instructions are superimposed with the local original three-phase current control instructions in the stationary coordinate system in terms of instantaneous values; the superimposed total current instructions are subjected to amplitude limiting processing to ensure that the amplitudes do not exceed the maximum allowable output current of the converter; and the fused total three-phase current instructions are generated, which contain both the original power control target and the oscillation suppression component of a specific frequency.

[0028] As a further scheme of the present application, the implementation of the coordinated suppression of the dominant oscillation frequency specifically comprises:

[0029] The fused total three-phase current instructions are taken as the given value of the inner loop current control; the current controller is adopted to accurately track and control the static error of the dominant oscillation frequency component; the voltage instruction output by the current controller is compared with the carrier signal to generate the corresponding pulse width modulation signal; the power switching device is driven by the pulse width modulation signal to make the converter output the current containing the specific anti-phase component, thereby achieving the active cancellation and coordinated suppression of the dominant oscillation frequency.

[0030] The output intensity of the anti-phase compensation current parameter is adjusted according to the monitoring result until the oscillation is completely eliminated, specifically comprising:

[0031] The latest oscillation amplitude characteristic quantity is acquired in real time; the decay rate of the current oscillation amplitude and the previous sampling period amplitude is calculated; when the decay rate is lower than the preset threshold, the amplitude parameter of the anti-phase compensation current parameter is increased by a preset step size; when the decay rate continuously exceeds the preset threshold, the amplitude parameter of the anti-phase compensation current parameter is decreased by a preset step size; when the oscillation amplitude is lower than the elimination threshold and remains stable, the amplitude parameter of the anti-phase compensation current parameter is gradually set to zero; and the frequency parameter of the compensation current instruction is dynamically adjusted according to the change of the oscillation frequency to ensure that the compensation frequency is always consistent with the dominant oscillation frequency.

[0032] The present application has the following beneficial effects:

[0033] (1) The present application is to construct a completely distributed oscillation suppression architecture, through each grid-connected converter unit, only exchange the standardized oscillation characteristic quantity (including frequency, amplitude, phase and confidence index) processed by standardization with the adjacent unit closely coupled with electricity and communication, and make decisions based on local information through distributed consistency algorithm. This design completely abandons the traditional centralized processing mode relying on central controller, not only eliminates the calculation bottleneck and communication delay existing in the data processing and instruction issuing process of central processor, avoids the risk of global system failure caused by single point failure of central controller. When local communication interruption or individual converter unit failure occurs in the system, the remaining units can still continue to work based on the latest neighborhood information, only form local optimization decision near the fault point, thereby improving the survival ability, adaptive ability and overall operation reliability of the system under abnormal working conditions.

[0034] (2) The present application adopts distributed architecture to realize multi-level collaborative processing of oscillation feature extraction, neighborhood negotiation and compensation injection, and dynamically adjusts output parameters through a precisely designed closed-loop optimization mechanism. This design enables the system to accurately track the dynamic characteristics of wideband oscillation, and adaptively adjusts the suppression strategy according to the real-time changes of oscillation intensity, ensuring the timeliness of the suppression measures and maintaining the stability of the control process, thereby effectively avoiding the common problems of response lag, over-compensation or under-compensation in traditional control methods, and realizing accurate suppression of complex oscillation modes. BRIEF DESCRIPTION OF DRAWINGS

[0035] The present application will be further described below with reference to the accompanying drawings.

[0036] Figure 1 is a flow chart of the system of the present application. DETAILED DESCRIPTION

[0037] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0038] Please refer to Figure 1 The present application is a wind-solar-storage co-site fast response joint regulation system, which comprises:

[0039] A real-time monitoring module is used to collect local electrical quantity data, and through real-time spectrum analysis, the frequency characteristics, amplitude characteristics and phase characteristics of abnormal oscillation are extracted to generate standardized oscillation characteristic quantity;

[0040] A neighborhood communication module is configured to interact with the grid-connected converter units within a predefined neighborhood range in a bidirectional manner to obtain the oscillation characteristics of the neighboring grid-connected converter units and construct a distributed oscillation characteristic set.

[0041] A cluster decision module is configured to reach a cluster consensus on the dominant oscillation frequency based on the distributed oscillation characteristic set through a distributed consensus algorithm and generate a corresponding anti-phase compensation current parameter.

[0042] An adaptive injection module is configured to fuse the anti-phase compensation current parameter with the original local current control instruction, generate a drive signal through pulse width modulation, and realize cooperative suppression of the dominant oscillation frequency.

[0043] A closed-loop optimization module is configured to continuously monitor the oscillation amplitude variation and adjust the output intensity of the anti-phase compensation current parameter according to the monitoring result until the oscillation is completely eliminated.

[0044] In the real-time monitoring module, local electrical quantity data is collected, and the frequency characteristics, amplitude characteristics, and phase characteristics of abnormal oscillation are extracted through real-time spectrum analysis to generate standardized oscillation characteristics, specifically including:

[0045] First, signal acquisition and preprocessing are performed. The real-time monitoring module continuously collects the instantaneous values of three-phase voltage and three-phase current at the grid-connected point at a super-sampling rate of 10,000 Hz through the high-precision sampling unit built in the grid-connected converter. These collected raw data are marked as raw signals. Subsequently, the raw signals are subjected to anti-aliasing filter processing through a fourth-order Butterworth low-pass filter with a cutoff frequency of 2,500 Hz to eliminate high-frequency noise interference and prevent spectral aliasing. The processed signals are segmented using the overlapping sliding window method, dividing the continuous signals into fixed data segments with a length of 200 milliseconds. A 50% overlap region is set between adjacent data segments, i.e., the first 100 milliseconds of each new data segment completely overlap with the last 100 milliseconds of the previous data segment. This processing method ensures the continuity of signal processing and ensures the complete capture of transient processes.

[0046] Secondly, signal decomposition and feature extraction are performed. An adaptive noise complete set decomposition process is performed on each 200 ms length data segment, which adaptively decomposes the signal into a series of intrinsic mode function components, each of which represents a specific oscillation mode in the signal. A high-precision spectrum analysis is performed on each intrinsic mode function component obtained by decomposition, and a spectrum analysis method based on fast Fourier transform is used, with a frequency resolution of 0.1 Hz. By analyzing the spectral characteristics of each component, abnormal oscillation frequency components contained therein are identified, which are frequency components deviating from the power frequency of 50 Hz and having an amplitude exceeding the background noise level by more than 3 decibels. For each identified abnormal oscillation frequency component, the corresponding amplitude information and phase information are recorded, with an amplitude accuracy of 0.01 ampere and a phase accuracy of 0.1 degree.

[0047] Then, feature standardization and confidence evaluation are performed. The extracted oscillation frequency value, amplitude information and phase information are packaged according to the preset standard data format to form a standardized oscillation feature quantity. The standardized oscillation feature quantity adopts a unified data structure, including the following fields: time stamp information accurate to the millisecond level, a unique device identifier code, and a comprehensive confidence index value. The comprehensive confidence index is obtained by weighted calculation of three technical parameters: the first parameter is the signal-to-noise ratio, obtained by calculating the ratio of signal power to noise power; the second parameter is the spectrum analysis convergence, obtained by evaluating the stability of frequency estimation values in three consecutive data segments; and the third parameter is the mode component stability, obtained by analyzing the energy concentration degree of the intrinsic mode function component. The three parameters are weighted and summed according to weights of 0.4, 0.3 and 0.3, respectively, to obtain a comprehensive confidence index value ranging from 0 to 1.

[0048] Finally, feature output and update are performed. The packaged standardized oscillation feature quantity is stored in a first-in-first-out data queue with a depth of 10, and the data queue is implemented using a ring buffer structure. The module takes out the latest standardized oscillation feature quantity data from the queue at a fixed time interval of 20 ms and outputs it to the subsequent neighborhood communication module. According to the feedback information, the parameter configuration of the signal processing is dynamically adjusted, including adaptively adjusting the overlap ratio of the sliding window according to the signal characteristics, with an adjustment range of 30% to 70%, to ensure the accuracy and real-time performance of feature extraction. The entire processing process is completed within 5 ms in a single data segment, ensuring the system's rapid response capability to external disturbances.

[0049] In the neighborhood communication module, the standardized oscillation feature quantity is bidirectionally exchanged with the grid-connected converter units in the predefined adjacent range, and the oscillation feature quantities of the adjacent grid-connected converter units are received to construct a distributed oscillation feature set, specifically including:

[0050] In the process of predefining the adjacent range, the neighborhood communication module first initializes a physical neighborhood table according to the actual electrical wiring topology of the wind-solar-storage same-field system, combined with the electrical distance parameters between each grid-connected converter unit. The physical neighborhood table contains information of all potential neighboring units in terms of electrical distance. The calculation of electrical distance is based on the impedance parameters between nodes, and units with electrical distance within 0.1 per unit are generally included in the initial neighborhood range. During system operation, the neighborhood communication module continuously monitors the communication link state between each potential neighboring unit in the physical neighborhood table, including transmission delay and packet loss rate. The transmission delay is monitored by sending time synchronization test frames, with a test frame interval of 100 milliseconds, and the average value is taken after 10 continuous monitoring cycles. The packet loss rate is calculated by counting the number of lost packets per 100 packets. Based on the monitoring results, the neighborhood communication module calculates the comprehensive weight index of each potential neighboring unit, which is determined by two factors: electrical coupling strength and communication quality. The electrical coupling strength is quantified by the voltage change of adjacent nodes caused by unit current change, and the communication quality is evaluated according to the transmission delay and packet loss rate. The transmission delay is required to be less than 50 milliseconds, and the packet loss rate is required to be less than 1%. Finally, the neighborhood communication module dynamically updates the neighborhood range according to the real-time calculation of the comprehensive weight index, and determines the grid-connected converter units with a comprehensive weight index higher than 0.8 as effective neighboring units, and establishes stable communication connection with these units. The communication connection adopts a dual-channel redundant design to ensure the reliability of data transmission.

[0051] In the process of constructing the distributed oscillation feature set, the neighborhood communication module first receives the standardized oscillation feature quantity sent from all valid adjacent units, and adds the local receiving timestamp and the source device identifier information to each received feature quantity, the receiving timestamp has an accuracy of 1 millisecond, and the source device identifier uses a 16-bit encoding format. Subsequently, the neighborhood communication module takes the timestamp of the local oscillation feature quantity as the reference to perform time synchronization alignment processing on all received standardized oscillation feature quantities. This processing uses a linear interpolation algorithm to uniformly interpolate the feature quantities arriving at different times to the same time reference point, effectively eliminating the timing error caused by communication delay, and the time synchronization accuracy is required to be 0.1 milliseconds. After completing the time synchronization, the neighborhood communication module performs consistency check and data fusion processing on the multiple time-aligned standardized oscillation feature quantities. The consistency check uses the 3σ criterion to eliminate abnormal standardized oscillation feature quantities that deviate significantly from the consensus of the cluster, and the abnormal judgment threshold is that the deviation of the feature quantity from the cluster mean is more than 3 times the standard deviation. For the remaining standardized oscillation feature quantities that pass the check, a weighted average processing is performed according to their confidence indicators. The feature quantity with a confidence indicator higher than 0.8 has a weight of 1, the feature quantity with a confidence indicator between 0.6 and 0.8 has a weight of 0.8, and the feature quantity with a confidence indicator lower than 0.6 has a weight of 0.5. A fusion feature quantity that can accurately represent the oscillation state of the local area is generated through weighted average. Finally, the neighborhood communication module combines the local standardized oscillation feature quantity and the fused neighborhood feature quantity to form a distributed oscillation feature set. The distributed oscillation feature set uses a unified data structure, including time series information, feature quantity data and corresponding confidence indicators, to provide complete data support for subsequent cluster decision-making.

[0052] All data collection, transmission and processing are completed in each operating cycle. The neighborhood communication module uses a distributed architecture design, and each grid-connected converter unit independently runs its own neighborhood communication module to achieve global collaboration through local data interaction. The communication protocol uses a special industrial communication protocol, and the data transmission rate is not less than 100 Mbps to ensure the real-time and reliability of data interaction. The neighborhood communication module also has a fault self-diagnosis function, which can automatically detect communication link abnormalities and perform corresponding processing. When it is detected that the communication of a certain adjacent unit is interrupted for more than 200 milliseconds, it is automatically removed from the list of valid adjacent units to ensure reliable operation of the system.

[0053] In the cluster decision-making module, based on the distributed oscillation feature set, the cluster consensus on the dominant oscillation frequency is reached through a distributed consistency algorithm, and the corresponding anti-phase compensation current parameters are generated, which specifically include:

[0054] In the process of reaching the cluster consensus on the dominant oscillation frequency through the distributed consistency algorithm, the cluster decision module first analyzes the feature quantity data in the received distributed oscillation feature set based on the received distributed oscillation feature set, and extracts the candidate value of the dominant oscillation frequency recognized by the unit. Each unit proposed candidate value is accompanied by the corresponding confidence weight, and the confidence weight is calculated according to the signal-to-noise ratio index of the feature quantity and the stability of the historical data. The confidence weight ranges from 0 to 1, and the accuracy is 0.01. Subsequently, each grid-connected converter unit exchanges the candidate value and the corresponding confidence weight information with all adjacent units through the existing communication connection, and the exchange process uses a dedicated data exchange protocol. After the exchange is completed, each unit processes through a multi-round iteration weighted average consistency protocol. In each iteration, each unit calculates a new frequency estimate value according to the candidate value and the confidence weight of itself and its adjacent units. When the confidence weight is higher than 0.8, the candidate value weight is 1.0, the weight between 0.6 and 0.8 is 0.7, and the weight below 0.6 is 0.3. After 5 to 10 rounds of iteration calculation, the output frequency values of all units gradually tend to be consistent, and the iteration termination condition is that the frequency change amount of two consecutive iterations is less than 0.05 Hz. When the variance of the frequency values output by all grid-connected converter units is less than the preset threshold value of 0.1 Hz, the system determines that the cluster consensus on the dominant oscillation frequency has been reached, and this consensus frequency is used as the reference frequency for subsequent compensation control.

[0055] In the process of generating the corresponding anti-phase compensation current parameters, the cluster decision module first determines the target frequency parameter of the compensation current according to the consensus frequency reached by the cluster, the target frequency is consistent with the consensus frequency, and the frequency accuracy requirement reaches 0.01 hertz. Subsequently, based on the oscillation amplitude information of the local and adjacent units in the distributed oscillation feature set, the initial amplitude parameter of the compensation current is calculated through a pre-defined amplitude-intensity mapping relationship. The mapping relationship adopts a piecewise linear function form, when the oscillation amplitude is below 0.1 per unit, the compensation current amplitude is 1.2 times the oscillation amplitude; when the oscillation amplitude is between 0.1 and 0.3 per unit, the compensation current amplitude is 1.0 times the oscillation amplitude; when the oscillation amplitude is higher than 0.3 per unit, the compensation current amplitude is 0.8 times the oscillation amplitude. At the same time, the cluster decision module takes the local detected oscillation phase as the reference, accurately measures the oscillation phase angle through digital signal processing technology, and the measurement accuracy reaches 0.1 degrees, and then superimposes a phase shift of one hundred and eighty degrees on this basis to generate the phase parameter of the compensation current. The phase shift processing adopts a circular calculation method modulo 360 degrees to ensure that the phase value always remains within the effective range of 0 to 360 degrees. Finally, the cluster decision module combines the determined target frequency parameter, the calculated amplitude parameter and the generated phase parameter into a complete anti-phase compensation current parameter, the anti-phase compensation current parameter adopts a standardized data format, including frequency value, amplitude, phase three main parameters, and corresponding time stamp and verification information, which is used for subsequent compensation execution link.

[0056] The entire processing flow from data reception to instruction generation is completed within the running period of each cluster decision module. The cluster decision module adopts a completely distributed decision-making mechanism, each grid-connected converter unit makes independent decisions based on local information, and global collaboration is achieved through a distributed consistency algorithm. The cluster decision module also has an adaptive adjustment function, which can dynamically adjust the decision parameters according to the system operating state, automatically adjust the weight distribution strategy and iteration termination condition when detecting changes in system oscillation characteristics, and ensure the accuracy and reliability of the decision results.

[0057] In the adaptive injection cluster decision module, the anti-phase compensation current parameters are fused with the original local current control instructions to generate drive signals through pulse width modulation, realizing collaborative suppression of the dominant oscillation frequency, which specifically includes:

[0058] In the process of fusing the anti-phase compensation current parameters with the local original current control instructions, the adaptive injection module first processes the anti-phase compensation current parameters from the cluster decision module. These parameters contain target frequency, amplitude and phase information, which are currently in the rotating coordinate system. The adaptive injection module converts the compensation current parameters in the rotating coordinate system to the stationary coordinate system through coordinate transformation processing to obtain the corresponding three-phase instantaneous compensation current instructions. The coordinate transformation adopts a standard transformation matrix, and the transformation angle is calculated in real time according to the actual phase angle of the system, with a calculation period of 100 microseconds. The three-phase instantaneous compensation current instructions obtained after transformation contain the instantaneous values of the A-phase, B-phase and C-phase three components, and the sampling rate of each component is consistent with the system control period, which is 10 kilohertz. Subsequently, the adaptive injection module superimposes the three-phase instantaneous compensation current instructions with the local original three-phase current control instructions in the stationary coordinate system. The superimposition process adopts a point-by-point addition method, and the current instruction value of each phase is algebraically added in each control period. After superimposition, the adaptive injection module limits the amplitude of the total current instruction, and the amplitude value is dynamically adjusted according to the actual operating parameters of the converter, and is usually set to 1.2 times the rated current of the converter. When the amplitude of the total current instruction exceeds the amplitude limit value, the adaptive injection module proportionally reduces the current instruction value of each phase to ensure that it is within the safe operating range. Finally, the adaptive injection module generates the fused total three-phase current instruction, which contains both the original active power and reactive power control targets and the oscillation suppression component of a specific frequency, providing accurate input signals for the subsequent pulse width modulation link.

[0059] In the process of achieving coordinated suppression of the dominant oscillation frequency, the adaptive injection module first takes the fused total three-phase current command as the given value of the inner loop current control. The current control loop uses a proportional-integral controller for processing, with a proportional coefficient of 0.5 and an integral time of 0.01 seconds. The controller accurately tracks and controls the dominant oscillation frequency component without static error, especially for oscillation frequencies in the range of 100 Hz to 1000 Hz. The output of the controller is a voltage command value, which includes the fundamental voltage component required to maintain normal system operation and the additional voltage component used to suppress oscillation. Subsequently, the adaptive injection module compares the voltage command output by the current controller with the carrier signal to generate the corresponding pulse width modulation signal. The carrier signal uses a triangular wave form with a frequency of 5000 Hz, and the amplitude is dynamically adjusted according to the DC bus voltage. The comparison process is realized through a specially designed comparator circuit, with a response time less than 1 μs. The generated pulse width modulation signal contains 6 independent drive signals, and the duty cycle of each signal is calculated in real time according to the corresponding voltage command value. Finally, the adaptive injection module drives power switching devices, including insulated gate bipolar transistors or metal oxide semiconductor field effect transistors, through these pulse width modulation signals. The drive circuit uses an isolation design, and the rise time and fall time of the drive signal are controlled within the preset range. The power switching devices switch according to the instructions of the drive signal, making the converter output a current containing a specific anti-phase component, which has the same amplitude and opposite phase as the oscillation current in the system, thereby achieving active cancellation and coordinated suppression of the dominant oscillation frequency.

[0060] In the closed-loop optimization module, the oscillation amplitude is continuously monitored, and the output intensity of the anti-phase compensation current parameters is adjusted according to the monitoring results until the oscillation is completely eliminated, including:

[0061] The closed-loop optimization module first acquires the latest oscillation amplitude characteristic quantity from the oscillation mode detection in real time. The closed-loop optimization module continuously updates at a sampling frequency of 1000 Hz, containing the amplitude information of the system oscillation at the current time. The closed-loop optimization module establishes a data buffer with a length of 100 sampling points, which is used to store the oscillation amplitude data in the last 100 milliseconds. When each new sampling point arrives, the closed-loop optimization module updates the corresponding buffer and removes the oldest historical data, ensuring that the analysis and processing are always based on the latest data. During data acquisition, the closed-loop optimization module performs validity check on the sampling values, removes invalid data caused by sampling abnormalities or communication interference, and ensures the accuracy and reliability of the data relied on for subsequent processing.

[0062] After obtaining the latest oscillation amplitude data, the closed-loop optimization module calculates the decay rate of the current oscillation amplitude and the previous sampling period amplitude. The calculation of the decay rate uses the difference method, that is, the current amplitude is subtracted from the amplitude of the previous sampling period, and then divided by the sampling time interval of 1 millisecond. The calculated decay rate is in units of per second per unit. The closed-loop optimization module simultaneously calculates the average decay rate over the last 10 sampling periods to eliminate the effects of accidental fluctuations. During the calculation process, the closed-loop optimization module records the historical trend of the decay rate and establishes a rate change curve for analyzing the dynamic response characteristics of the system. All these calculations are completed within each sampling period.

[0063] According to the calculated decay rate results, the closed-loop optimization module executes the corresponding parameter adjustment strategy. When the decay rate is lower than the preset threshold of 0.1 per second per unit, it is judged that the suppression effect is insufficient, and the amplitude parameter of the anti-phase compensation current parameter is gradually increased by 0.05 per unit step. The increase amount is proportionally adjusted according to the difference between the current amplitude and the target amplitude, and the maximum single adjustment amplitude does not exceed 5% of the rated current. When the decay rate continuously exceeds the preset threshold of 0.2 per second per unit, it is judged that there is over-compensation, and the amplitude parameter of the anti-phase compensation current parameter is reduced by 0.03 per unit step. A minimum amplitude limit is set during the reduction process to ensure that negative values do not occur. All adjustment operations use a ramp change method to avoid step changes that can cause shocks to the system.

[0064] When the oscillation amplitude is monitored to be below the elimination threshold of 0.02 per unit, and remains stable for 10 consecutive sampling periods, the closed-loop optimization module starts the exit program. The exit process uses a gradual approach to gradually reduce the amplitude parameter of the anti-phase compensation current parameter at a rate of 0.01 per second per unit until it is completely zeroed out. During the entire exit process, the closed-loop optimization module continuously monitors the oscillation amplitude, and if the oscillation reappears, it immediately stops the exit process and restores the appropriate compensation strength. At the same time, the closed-loop optimization module dynamically adjusts the frequency parameter of the compensation current command according to the real-time changes in the oscillation frequency, with a frequency tracking accuracy of 0.01 hertz, ensuring that the compensation frequency always matches the dominant oscillation frequency and avoiding a decrease in suppression effect due to frequency deviation.

[0065] The entire closed-loop optimization module is synchronized with the system sampling period. The closed-loop optimization module has a built-in self-diagnosis function that can monitor the effectiveness of the adjustment process in real time, and automatically switches to a backup control strategy when the adjustment strategy fails. All adjustment parameters and operating states are uploaded in real time through a data interface for monitoring system recording and analysis. The closed-loop optimization module also has a parameter self-adaptive function that can automatically optimize various thresholds and step sizes based on system operation experience, continuously improving control accuracy and response speed.

[0066] The working principle of the application is: the local electrical quantity data is collected by the real-time monitoring module, the frequency, amplitude and phase characteristics of abnormal oscillation are extracted by using oversampling and adaptive noise perfect set decomposition technology, and standardized oscillation characteristic quantities containing time stamp, device identifier and confidence index are generated; the characteristic quantities are bidirectionally interacted with the converter units in the predefined adjacent range through the neighborhood communication module, the dynamic neighborhood updating mechanism based on electrical coupling strength and communication quality is adopted, and the distributed oscillation characteristic set is constructed through time synchronization alignment and weighted average fusion processing; the cluster decision module performs multiple rounds of iterative negotiation based on the distributed consistency algorithm, reaches the cluster consensus on the dominant oscillation frequency, and generates the anti-phase compensation current parameters according to the amplitude-intensity mapping relationship and the phase offset principle; the compensation parameters are fused with the original current command in the stationary coordinate system through the adaptive injection module, and the driving signal is generated after the amplitude limiting processing by using the enhanced proportional integral controller and the pulse width modulation technology; the oscillation amplitude change is monitored in real time through the closed-loop optimization module, the compensation parameter output strength is dynamically adjusted according to the decay rate, and the gradual exit strategy is adopted to realize the complete elimination of the oscillation.

[0067] The above describes one embodiment of the application in detail, but the content described is only the preferred embodiment of the application and cannot be considered as limiting the scope of the implementation of the application. Any equivalent changes and improvements made within the scope of the application shall still belong to the patent coverage range of the application.

Claims

1. A rapid response joint control system for wind, solar, and energy storage, characterized in that: include: The real-time monitoring module is used to collect local electrical quantity data and extract the frequency characteristics, amplitude characteristics and phase characteristics of abnormal oscillations through real-time spectrum analysis to generate standardized oscillation characteristic quantities. The neighborhood communication module is used to perform bidirectional interaction of standardized oscillation characteristic quantities with grid-connected converter units within a predefined adjacent range, and to receive the oscillation characteristic quantities of adjacent grid-connected converter units to construct a distributed oscillation characteristic set. The cluster decision module is used to reach a cluster consensus on the dominant oscillation frequency based on a distributed oscillation feature set and a distributed consensus algorithm, and to generate corresponding anti-phase compensation current parameters. The process of achieving cluster consensus on the dominant oscillation frequency through a distributed consensus algorithm specifically includes: Based on the distributed oscillation feature set, each grid-connected converter unit first independently proposes its identified candidate value for the dominant oscillation frequency; each grid-connected converter unit exchanges the candidate value and its confidence weight with its neighboring grid-connected converter units; through a multi-round iterative weighted average consensus protocol, the output values ​​of all units tend to be consistent; when the variance of the frequency values ​​output by each grid-connected converter unit is less than a preset threshold, it is determined that a cluster consensus on the dominant oscillation frequency has been reached. The generation of the corresponding reverse-phase compensation current parameters specifically includes: Based on the agreed-upon cluster consensus frequency, the target frequency of the compensation current is determined; based on the oscillation amplitude information of the local and neighboring regions in the distributed oscillation feature set, the initial amplitude parameter of the compensation current is calculated through a predefined amplitude-intensity mapping relationship; using the locally detected oscillation phase as a reference, a phase offset of 180 degrees is superimposed to generate the phase parameter of the compensation current; the target frequency, amplitude parameter, and phase parameter are combined together to form the complete anti-phase compensation current parameter. An adaptive injection module is used to fuse the inverse compensation current parameters with the local original current control command, and generate a drive signal through pulse width modulation to achieve coordinated suppression of the dominant oscillation frequency. A closed-loop optimization module is used to continuously monitor the change in oscillation amplitude and adjust the output intensity of the reverse-phase compensation current parameter according to the monitoring results until the oscillation is completely eliminated.

2. The wind-solar-storage co-location rapid response joint control system according to claim 1, characterized in that, The process for obtaining the standardized oscillation characteristic is as follows: The instantaneous values ​​of voltage and current at the grid connection point are continuously collected at a preset oversampling rate and recorded as the original signal. The original signal is subjected to anti-aliasing filtering. The continuous signal is divided into data segments of fixed length using an overlapping sliding window method, with a preset ratio of overlapping area between adjacent data segments. Adaptive noise complete set decomposition is performed on each data segment to decompose the signal into multiple intrinsic mode function components. High-precision spectrum analysis is performed on each component to identify the abnormal oscillation frequency components and their corresponding amplitude and phase information. The extracted oscillation frequency, amplitude, and phase information are encapsulated into standardized oscillation feature quantities according to a preset format. The standardized oscillation feature quantities include timestamps, device identifiers, and confidence indices. The confidence indices are calculated by comprehensively considering the signal-to-noise ratio, spectral analysis convergence, and modal component stability. The standardized oscillatory features are stored in a first-in-first-out queue, and the latest standardized oscillatory features are output at fixed time intervals.

3. The wind-solar-storage co-location rapid response joint control system according to claim 1, characterized in that, The process of predefining adjacent ranges specifically includes: Based on the electrical wiring topology of the wind-solar-storage co-location and the electrical distance between each grid-connected converter unit, a physical neighborhood table is initialized. During the operation of the wind-solar-storage co-location, the transmission delay and data packet loss rate of the communication links with each potential adjacent unit are monitored in real time. The comprehensive weight index of electrical coupling strength and communication quality is calculated. The electrical coupling strength is characterized by the voltage change of adjacent nodes caused by a unit current change. The neighborhood range is updated, and grid-connected converter units with a comprehensive weight index higher than a preset threshold are identified as valid adjacent units, and stable communication connections are established.

4. The wind-solar-storage co-location rapid response joint control system according to claim 1, characterized in that, The construction of the distributed oscillation feature set specifically includes: The system receives standardized oscillation features and appends a receiving timestamp and source device identifier to each feature. Using the timestamp of the local oscillation feature as a reference, it performs time synchronization alignment on all standardized oscillation features to eliminate timing errors caused by communication delays. It then performs consistency verification and data fusion on the time-aligned standardized oscillation features, removing abnormal standardized oscillation features that deviate from the cluster consensus. Finally, it performs a weighted average of the remaining standardized oscillation features based on confidence levels to generate a fused feature that characterizes the oscillation state of a local area. The local standardized oscillation features and the fused feature are then combined to form a distributed oscillation feature set.

5. The wind-solar-storage co-location rapid response joint control system according to claim 1, characterized in that, The process of integrating the reverse-phase compensation current parameters with the existing local current control commands specifically includes: The reverse-phase compensation current parameters are transformed from the rotating coordinate system to the stationary coordinate system to obtain the three-phase instantaneous compensation current command. The obtained three-phase instantaneous compensation current command is then superimposed with the original local three-phase current control command in the stationary coordinate system. The superimposed total current command is subjected to amplitude limiting to ensure that its amplitude does not exceed the maximum allowable output current of the converter. A fused total three-phase current command is then generated, which includes both the original power control target and an oscillation suppression component of a specific frequency.

6. The wind-solar-storage co-location rapid response joint control system according to claim 1, characterized in that, The aforementioned coordinated suppression of the dominant oscillation frequency specifically includes: The combined total three-phase current command is used as the setpoint for the inner loop current control; the current controller is used to accurately track and control the dominant oscillation frequency component with zero steady-state error; the voltage command output by the current controller is compared with the carrier signal to generate a corresponding pulse width modulation signal; the power switching device is driven by the pulse width modulation signal to make the converter output current containing a specific anti-phase component, thereby realizing active cancellation and cooperative suppression of the dominant oscillation frequency.

7. The wind-solar-storage co-location rapid response joint control system according to claim 1, characterized in that, The step of adjusting the output intensity of the reverse-phase compensation current parameter based on the monitoring results until the oscillation is completely eliminated specifically includes: The system acquires the latest oscillation amplitude characteristics in real time; calculates the decay rate of the current oscillation amplitude compared to the amplitude of the previous sampling period; when the decay rate is lower than a preset threshold, it increases the amplitude parameter of the inverse compensation current parameter by a preset step size; when the decay rate continues to be higher than the preset threshold, it decreases the amplitude parameter of the inverse compensation current parameter by a preset step size; when the oscillation amplitude is lower than the elimination threshold and remains stable, it gradually reduces the amplitude parameter of the inverse compensation current parameter to zero; at the same time, it dynamically adjusts the frequency parameter of the compensation current command according to the change of the oscillation frequency to ensure that the compensation frequency is always consistent with the dominant oscillation frequency.

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