Network construction type converter control method, system and equipment with low communication cost and medium

Abstract

The invention discloses a network construction type converter control method, system and device with low communication cost and a medium. The method comprises the following steps: constructing a frequency-voltage-power closed-loop control model and presetting an operation parameter range; acquiring a local operation amount in real time, comparing the local operation amount with a last broadcast value, calculating an error norm, and determining whether to trigger a communication event; when a communication event occurs, estimating a system characteristic quantity and a coupling strength upper bound; dynamically adjusting a trigger threshold and a trigger function parameter, and ensuring a lower bound of an event interval; superposing a neighbor node state correction item on the basis of local droop control, and updating only when an event is triggered; soft / hard amplitude limiting is carried out on voltage, frequency and power, when an operation point is close to an out-of-limit interval, communication trigger frequency is improved, and a low communication mode is recovered after out-of-limit is relieved; and continuing the low communication mode after the disturbance is eliminated. The method can provide key data support for power grid construction type control, and has important significance in the field of power system construction type control.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of converter control, and particularly relates to a low-communication-cost grid-forming converter control method, system, device and medium, which is suitable for the cooperative operation of multiple grid-forming converters in an islanded or weakly interconnected power system. BACKGROUND

[0002] Grid-forming converters are widely used in microgrids and weakly interconnected power systems with high penetration of renewable energy sources due to their ability to actively establish voltage and frequency references, provide virtual inertia and voltage support. To ensure the cooperative operation of multiple grid-forming converters, achieve frequency stability, voltage recovery and power sharing, control strategies are generally divided into virtual synchronous machine control, droop control, model predictive control and data-driven control based on reinforcement learning. The first two methods are simple and easy to implement, but the control parameters are fixed and usually rely on high-frequency communication to complete secondary voltage and frequency recovery; model predictive control and data-driven methods can adapt to uncertainties, but they require centralized computation or high-bandwidth real-time data support.

[0003] The stable operation of microgrids and weakly interconnected power systems highly depends on the reliability and scalability of the control architecture. Centralized control has the risk of single-point failure and poor scalability, and has been gradually replaced by distributed control. Distributed control achieves global goals through information exchange between local controllers, improving system flexibility and fault tolerance. However, traditional distributed methods often use fixed-period sampling and full-state communication, which not only occupies a large amount of communication bandwidth, but also easily causes delays, packet loss and other problems, affecting system dynamic performance and increasing network security risks.

[0004] Especially in weak grids dominated by large-scale GFM, the update frequency of control commands directly affects system stability. Traditional periodic communication strategies have the problem of redundant data transmission, and existing event-triggered methods still have deficiencies in terms of complete distribution, no global parameter dependence, and explicit performance lower bound guarantee. Therefore, there is an urgent need for a grid-forming converter control method that has frequency-voltage stability control, power sharing, dynamic adaptive triggering and safety protection functions under low communication conditions, to meet the stable operation requirements under communication constraints, grid topology changes and disturbance environments. SUMMARY

[0005] To solve at least one of the problems existing in the prior art, the present application provides a low-communication-cost grid-forming converter control method, system, device and medium, which is suitable for the cooperative operation of grid-forming converters in an islanded or weakly interconnected power system with 100% new energy power supply, and can provide key data support for grid-forming control in the field of power system grid-forming control, which has important significance.

[0006] In order to achieve the object of the present application, the present application provides a low-communication-cost network-configuration-type converter control method, comprising the following steps: A low-communication-cost network-configuration-type converter control method, comprising the following steps: S1, a frequency-voltage-power closed-loop control model is constructed, and an operating parameter range is preset; S2, local operating quantities are collected in real time, and compared with the last broadcast value, an error norm is calculated, and a trigger function is formed by combining an exponential decay threshold to determine whether to trigger a communication event; S3, when the communication event occurs, system characteristic quantities and coupling strength upper bounds are estimated based on local measurement results; S4, the exponential decay threshold and the trigger function parameters are dynamically adjusted according to the stability margin to ensure the lower bound of the event interval; S5, on the basis of local droop control, a neighbor node state correction term is superimposed, and is only updated when the event is triggered, so as to realize the coordinated recovery of multi-machine frequency and voltage and power distribution; S6, voltage, frequency and power are implemented by soft / hard limiting, when the operating point approaches the limiting interval, the communication triggering frequency is increased, and after the limiting is removed, the low communication mode is restored; S7, after the disturbance is eliminated, the low communication mode is continued until the next trigger condition is met.

[0007] Further, the frequency-voltage-power closed-loop control model comprises: Taking the rated frequency of the system as the reference, the frequency instruction is calculated by the primary frequency droop coefficient according to the active power deviation; Taking the rated voltage of the system as the reference, the voltage instruction is calculated by the voltage droop coefficient according to the reactive power deviation The average values of the active power and the reactive power are extracted by using a low-pass filter, and are compared with the frequency instruction and the voltage instruction to obtain the deviation input to the droop control; The instantaneous value of the converter output current is controlled by the inner loop, and the converter output voltage is controlled by the outer loop.

[0008] Further, in step S2, the following sub-steps are included: Local operating parameters are obtained, including real-time frequency, bus voltage, active power and reactive power, to form an operating parameter set; The operating parameters broadcasted last time are saved, and the weighted Euclidean norm error of the current operating quantity and the last broadcast value is calculated; The exponential decay threshold value is calculated based on the initial threshold value, the minimum threshold value allowed and the decay coefficient; ​Forming trigger function: if the weighted Euclidean norm error is greater than the exponential decay threshold value, it is determined that the event needs communication, and the current operating parameter set is immediately broadcast to the neighbor node and the trigger time is recorded; if the weighted Euclidean norm error is less than or equal to the exponential decay threshold value, it is kept silent and no data is sent.

[0009] Further, in step S3, when the communication event occurs, the system characteristic quantity and the coupling strength upper bound are estimated based on the local measurement results by using a distributed consistency algorithm, specifically: According to the operating parameter set and the droop control parameter obtained by the current sampling, a local linearized state space model is calculated; The maximum real part eigenvalue and the condition number are obtained by calculating the closed-loop eigenvalue set of the system matrix locally; When the event is triggered, the maximum real part eigenvalue and the condition number are sent to the directly adjacent node through point-to-point communication, the adjacent node sends its characteristic quantity at the same time, and after mutual exchange, the maximum consistent algorithm iteration is performed to obtain the maximum real part eigenvalue and the maximum condition number of the whole network; Based on the maximum real part eigenvalue and the maximum condition number of the whole network, the coupling strength upper bound of the system is obtained.

[0010] Further, in step S4, the grid-type converter receives the maximum real part eigenvalue and the maximum condition number of the whole network calculated in step S3, and dynamically modifies the event trigger criterion combined with the coupling strength upper bound, including: Based on the maximum real part eigenvalue of the whole network and the preset stability safety threshold, a stability margin coefficient is defined; The stability margin coefficient is compared with the determination boundary of sufficient or insufficient margin to adjust the initial value parameter of the exponential decay threshold.

[0011] Further, step S5 includes the following sub-steps: The frequency-voltage-power closed-loop control model established in step S1 is used to calculate the frequency command and the voltage command respectively; Based on the state difference of the adjacent node, a correction term of voltage and frequency is constructed; The active power and the reactive power are respectively allocated in proportion; The correction term is superimposed to the local control reference:

[0012] wherein, , is the frequency and voltage control command after joining the distributed correction, , is the correction gain coefficient of frequency and voltage respectively, is the frequency command, is the voltage command.

[0013] Further, step S7 includes: Continuously monitor the local operating quantity and the state information of the neighbor nodes, if all operating quantities are within the safe range and the deviation from the reference value is lower than the static deviation threshold, it is determined that the disturbance has been eliminated; When the disturbance is eliminated, the initial threshold of event triggering is restored to the set normal threshold value, the threshold attenuation coefficient is set to a low value, the triggering interval is extended, and communication is performed only when the triggering function of step S2 is triggered; In the case that there is no event triggering within the preset time, the health status package is periodically sent to the neighbor nodes once.

[0014] The application provides a low-communication-cost network-constructing type converter control system, which comprises the following modules: A local measurement and execution module is used for collecting voltage and current signals of an output end of the network-constructing type converter in real time, calculating instantaneous active power and reactive power, detecting a local operating frequency and a bus voltage, inputting the collected operating quantity into a local execution unit, and driving a power conversion unit to perform adjustment according to a control instruction; An event-triggered communication module is used for calculating a deviation norm of a current operating quantity from a last broadcast value, generating an exponential attenuation threshold value, determining whether the threshold value is exceeded and triggering a communication event, and sending the current operating data to neighbor nodes through a point-to-point communication link; An adaptive parameter estimation module is used for calculating a linearized system matrix according to a local operating state, calculating a maximum real part eigenvalue and a condition number, exchanging information with the neighbor nodes to obtain a maximum eigenvalue and a condition number of the whole network, and estimating an upper bound of system coupling strength; A triggering parameter updating module is used for judging whether the system state needs to increase or decrease a triggering frequency according to a stability margin coefficient, dynamically adjusting an initial threshold value and an exponential attenuation coefficient, and setting and executing a minimum time interval of an event; A distributed coordination control module is used for calculating a frequency instruction and a voltage instruction based on a local power deviation, receiving an operating state of the neighbor nodes, calculating a frequency and a voltage correction term, distributing active and reactive power reference values according to a power ratio, and outputting the corrected control instruction to the local execution module to realize collaborative operation of multiple machines; A protection and limiting module is used for monitoring a frequency, a voltage, an active power and a reactive power in real time and comparing them with preset limit values, executing a soft limiting strategy when approaching an over-limit, executing a hard limiting or emergency shutdown strategy when over-limit, increasing a communication triggering frequency during the over-limit period, and restoring the low communication mode after the over-limit period.

[0015] The application provides a device, the device comprising a processor and a memory, the memory being used for storing instructions or computer programs, and the processor being used for executing the instructions or computer programs in the memory to enable the device to perform the steps of the method.

[0016] The application provides a computer readable storage medium, wherein instructions are stored in the computer readable storage medium, and when the instructions are run on a device, the device is caused to execute steps of the method.

[0017] The application has the following beneficial effects relative to the prior art: (1) The application uses an event triggering mechanism based on an exponential decay threshold and exponential decay, and only broadcasts data when a running state changes significantly, thereby avoiding redundant information exchange of traditional periodic communication and significantly reducing communication load.

[0018] (2) The application uses local calculation and distributed consistency algorithm to realize network stability margin estimation, does not depend on global communication topology matrix eigenvalue and other centralized information, and can maintain scalability and robustness of the control architecture when the system topology changes, a large number of nodes are accessed or nodes are exited. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 A flowchart of a low-communication-cost network-type converter control method provided for an embodiment of the application.

[0020] Figure 2 A module schematic diagram of a low-communication-cost network-type converter control system provided for an embodiment of the application.

[0021] Figure 3 A schematic diagram of an island power grid powered by 100% new energy in an embodiment of the application.

[0022] Figure 4 A control result comparison diagram of different methods. DETAILED DESCRIPTION

[0023] To make the purpose, technical scheme and advantages of the embodiments of the application clearer, the technical scheme in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are some of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative work fall within the protection scope of the application.

[0024] Please refer to Figure 1 The low-communication-cost network-type converter control method provided by the embodiment of the application includes the following steps: S1) Establish a frequency-voltage-power closed-loop control model in each converter, and preset a running parameter range.

[0025] The operating parameter range includes upper and lower limits for frequency, upper and lower limits for voltage, and power limits.

[0026] This step establishes a closed-loop control framework, including droop control, power control, voltage regulation, and frequency regulation, within the local controller of each grid-connected converter. This closed-loop control framework is constructed through the following sub-steps: S11, at the system rated frequency Based on the active power deviation, the primary frequency droop coefficient is used as a benchmark. Frequency calculation instructions , Active power This is a reference value for the target active power. S12, based on the system rated voltage Based on the reactive power deviation, the voltage droop coefficient is used as a reference. Calculate voltage command , Reactive power This is a reference value for reactive power; S13. Use a low-pass filter to extract active power. With reactive power The average value, and compared with the reference values ​​of frequency and voltage, i.e., the frequency command. Voltage command The deviation is compared and input to the droop control. S14. The instantaneous value of the converter output current is controlled by the inner loop, and the output voltage of the converter is controlled by the outer loop to ensure dynamic response and steady-state accuracy.

[0027] S2) Event Trigger Monitoring: Real-time collection of local operating quantities of grid-type converter nodes, comparison with the previous broadcast value, calculation of error norm, and formation of trigger function in combination with exponential decay threshold. In the trigger function, a communication event is triggered when the error exceeds the threshold, and remains silent when it does not exceed the threshold.

[0028] In one embodiment of the present invention, each grid-connected converter has an event-triggered communication determination module in its local controller, and the event-triggered communication determination module is configured to perform the following steps: S21. Local operating parameter acquisition, real-time frequency. Bus voltage Active power and reactive power , forming nodes Set of running parameters The sampling period is no less than 50 ms; S22. Save the set of operating parameters from the last external broadcast. Calculate the weighted Euclidean norm error between the current running volume and the last broadcast value. :

[0029] in, , , , These are the weighting coefficients for frequency, voltage, active power, and reactive power, respectively. , , , The first Frequency, voltage, active power, reactive power at any given moment , , , These are the frequency, voltage, active power, and reactive power of the last external broadcast; S23. Calculation of Exponential Decay Threshold Value : The initial threshold is triggered based on a preset event. Minimum allowed threshold value and attenuation coefficient (Control the threshold descent speed), combined with the time interval since the last triggered event. Calculate the exponential decay threshold value at the current time. Its calculation formula is ; S24. Forming the trigger function: The function calculated in step S22... Compared with the current exponential decay threshold value calculated in step S23 Compare the results to determine the trigger function; like This is then determined to be an event requiring communication, and the current set of operating parameters is immediately broadcast. Reach neighboring nodes and record the trigger time; if Then remain silent and do not send data.

[0030] S3) Stability Margin Estimation: When a communication event occurs, a distributed consensus algorithm is used to estimate the system's characteristic quantities and the upper bound of coupling strength based on local measurement results. Specifically: S31. Based on the set of operating parameters obtained from the current sampling. And droop control parameters, calculate the local linearized state-space model :

[0031] in, This is the local calculation system matrix (including frequency, voltage, and power dynamic equation coefficients). For the input matrix, To control the input vector; S32. Using the Jacobi method, the system matrix is ​​calculated locally. The closed-loop eigenvalue set is used to obtain local feature quantities, including the eigenvalue with the largest real part. and condition numbers ; S33. When the event is triggered, the local feature quantity—the eigenvalue with the largest real part—is... and condition numbers The feature values ​​are sent to the directly adjacent nodes via point-to-point communication. The directly adjacent nodes simultaneously send their feature values, and after the two sides exchange them, the maximum consistency algorithm is iterated.

[0032] in, Indexing neighboring nodes, For the number of iteration rounds; if the communication topology is a multi-hop network, after a finite number of iterations, each node obtains the eigenvalue with the largest real part of the entire network. With the maximum condition number ; , The first Round iteration node The eigenvalue with the largest real part and the condition number. , The first Round iteration node The eigenvalue of the largest real part and the condition number; S34. Calculate the upper bound of the system coupling strength using the stability criterion formula based on the characteristic of the largest real part of the entire network. :

[0033] S4) Adaptive update of trigger parameters: The exponential decay threshold and trigger function parameters are dynamically adjusted based on the stability margin to ensure the lower bound of the event interval. Specifically, in the trigger parameter update module of each grid-type converter, the maximum real part eigenvalue and the maximum condition number of the entire network calculated in step S3 are received, and the event triggering criterion is dynamically corrected in combination with the upper bound of the coupling strength. The steps are as follows: S41. Set the normal threshold value When the system is running normally and stably, the initial threshold value for event triggering is... Take the standard threshold value , serving as the baseline for triggering parameters; In one embodiment of the present invention, a conventional threshold value 0.9 p.u. - 1.1 p.u.

[0034] S42, defining stability margin coefficient is a preset stability safety threshold; represents that the system is stable, represents that the system is in a critical or unstable state; S43, threshold adjustment, if , increase the event trigger initial threshold value ; if , reduce the event trigger initial threshold value wherein, and are the margin sufficient / insufficient determination boundaries, and are the upper and lower adjustment proportions of the threshold.

[0035] S5) Distributed coordinated control: on the basis of the present droop control, a neighbor node state correction term is superimposed, which is only updated at the event trigger, to realize the collaborative recovery and power distribution of multi-machine frequency and voltage, specifically: S51, using the frequency-voltage-power closed-loop control model established in step S1) to calculate the local frequency reference value and voltage reference value, i.e. frequency instruction , voltage instruction S52, based on the state difference of adjacent nodes to construct the correction term of voltage and frequency:

[0036] wherein, , are the correction frequency and voltage of node , , are the frequency and voltage of node , , are the coupling weights of adjacent nodes and , is the total number of nodes; S53, through the frequency-active droop relationship, according to the primary frequency droop coefficient , the active power is proportionally distributed; through the voltage-reactive droop relationship, according to the voltage droop coefficient , the reactive power is proportionally distributed.​​​​​​

[0037] S54, superimpose the correction term to the local control reference:

[0038] wherein, , are the frequency and voltage control instructions after adding the distributed correction, , are the correction gain coefficients of frequency and voltage, respectively.

[0039] S6) Protection and amplitude limiting: soft / hard limiting is performed on voltage, frequency, and power, when the operating point approaches the over-limit interval, the communication triggering frequency is increased, and after the over-limit is removed, the low communication mode is restored (i.e. the closed-loop control realized by the frequency-voltage-power closed-loop control model of step S1).

[0040] In one embodiment of the present application, soft limiting: when the system voltage, frequency, and power exceed the set safety limit value of 0.97 times, the change of the corresponding parameter is gradually slowed down; hard limiting: when the system voltage, frequency, and power exceed the set safety limit value, the cooperative control strategy of steps S2) to S6) is immediately executed.

[0041] S7) Cycle operation: continue low communication mode after disturbance elimination until the next trigger condition is met, specifically: S71, continuously monitor the local operating quantities and the state information of the neighbor nodes, if all operating quantities are within the safe range and the deviation from the reference value is lower than the static deviation threshold, it is determined that the disturbance has been eliminated; S72, when the disturbance is eliminated, the event trigger initial threshold is restored to the regular threshold value set in S4), the threshold decay coefficient is set to a low value (such as between 0.01-0.05), the trigger interval is extended, and communication is performed only when the trigger condition of S2) is met; S73, in the case of no event triggering for a long time, a health status package is periodically (such as every 5-10 seconds) sent to the neighbor nodes, including: frequency, voltage, active power, reactive power, and power supply status.

[0042] In one embodiment of the present application, a low-communication-cost network-type converter control system is provided for implementing the method provided in the foregoing embodiments, the system includes the following modules: The local measurement and execution module includes a voltage sensor for collecting voltage, a current sensor for collecting current, a frequency detection unit for detecting frequency, a power detection unit for detecting power, and a local execution unit for executing local control (to execute the content of step S1), an internal integrated analog-to-digital converter and a digital signal processor, which collect three-phase voltage and current signals at the output end of the networked converter in real time, calculate instantaneous active power and reactive power, detect the local operating frequency and bus voltage, input the collected operating quantities into the local execution unit, and drive the power conversion unit to perform adjustment according to the control instruction; The event-triggered communication module includes an error calculation unit, a threshold generation unit, a communication interface, and a buffer queue, which are used to calculate the error norm of the current operating quantity and the last broadcast value, generate an exponentially decaying threshold (threshold value ), determine whether the threshold is exceeded and trigger a communication event, and send the current operating data to the neighbor node through a point-to-point communication link; The adaptive parameter estimation module includes a local state space model construction unit, an eigenvalue solving unit, a condition number calculation unit, and a distributed consistency operation unit, which calculate the linearized system matrix and the maximum real part eigenvalue and condition number according to the local operating state, exchange information with the adjacent nodes to obtain the maximum eigenvalue and condition number of the whole network through a distributed consistency algorithm, and estimate the upper bound of the system coupling strength based on the calculation results; The trigger parameter update module includes a margin calculation unit, a threshold adjustment unit, and a minimum event interval control unit, which determine whether the system state needs to increase or decrease the trigger frequency according to the stability margin coefficient, dynamically adjust the initial threshold value, set and execute the minimum time interval of the event; The distributed coordinated control module includes a droop control calculation unit, a neighbor state receiving unit, a distributed correction calculation unit, and a power distribution optimization unit, which calculate the frequency reference value and the voltage reference value based on the local power deviation, receive the operating state of the neighbor node, calculate the frequency and voltage correction terms, distribute the active and reactive power reference values in proportion to the power, and output the corrected control instruction to the local execution unit to realize coordinated operation of multiple machines; The protection and limiting module includes an operating quantity monitoring unit, a soft limiting unit, a hard limiting unit, and a communication strategy switching unit, which monitor the frequency, voltage, active power, and reactive power in real time and compare them with the preset limit value, execute the soft limiting strategy when approaching the limit, execute the hard limiting or emergency shutdown strategy when exceeding the limit, increase the communication trigger frequency during the limit exceeding period, and restore the low communication strategy after the limit is removed.

[0043] The system comprises a local measurement and execution module, an event-triggered communication module, an adaptive parameter estimation module, a distributed coordinated control module and a safety protection module, a point-to-point sparse communication network is formed between each converter node, without a centralized controller, the frequency-voltage coordinated control and power distribution of multiple networked converters can be realized without high-frequency communication, the number of communication events is significantly reduced, and the stability and robustness of the system in a communication limited scene are improved.

[0044] In one of the embodiments of the present application, a device is provided, comprising a processor and a memory, the memory is used to store instructions or computer programs, and the processor is used to execute the instructions or computer programs in the memory to make the device execute the steps of the method in the foregoing embodiments.

[0045] In one of the embodiments of the present application, a computer readable storage medium is provided, and the computer readable storage medium stores instructions, when the instructions are run on a device, the device executes the steps of the method in the foregoing embodiments.

[0046] In one of the embodiments of the present application, an example analysis is carried out by using a system as shown in Figure 3 The system adopts an island mode of operation, contains three distributed photovoltaic power stations and one distributed wind turbine generator set, each device is connected through a grid following type (GFL) converter, and there is no communication between each unit. The voltage and frequency reference values are completely provided by three grid forming type (GFM) energy storages, and these devices share a dedicated communication layer, so that adjacent energy storage units can exchange state information. The system parameter configuration is as follows: the rated frequency is 50 Hz, and the rated voltage is 1.0 p.u. The proposed event-triggered distributed control strategy is evaluated by comprehensive simulation, and compared with traditional control methods (continuous control and centralized control), and the results are shown in Table 1 and Figure 4 .

[0047] Table 1 Comparison of indicators of different methods

[0048] As shown in Table 1, the maximum frequency deviation of the method of the present application is 0.8222 Hz, which is obviously better than 1.0650 Hz of the continuous control and 1.0194 Hz of the centralized control; the maximum speed (RoCoF) is only 23.52 Hz / s, which is obviously reduced compared with the continuous control (26.55 Hz / s) and the centralized control (34.45 Hz / s), effectively reducing the dynamic impact of the system in the disturbance process. The maximum power imbalance of the three methods under this working condition is 1.35 p.u., indicating that the performance in power distribution accuracy is equivalent.

[0049] In terms of steady-state performance, the frequency control error of the method of this invention is 0.0072 Hz, which is better than the 0.0085 Hz of continuous control and close to the 0.0022 Hz of centralized control. Meanwhile, the method of this invention only experiences 116 communication events throughout the entire operating cycle, a reduction of approximately 92% compared to the 1449 events in continuous control, significantly reducing the communication burden. Compared to centralized control, this invention retains the scalability and resistance to single-point failures of the distributed structure, does not rely on a centralized control center, and possesses higher reliability. The results show that this invention can significantly reduce communication load under communication-constrained conditions while maintaining excellent frequency, voltage stability, and power distribution performance, balancing communication efficiency, dynamic response, and system security.

[0050] The above embodiments verify that the solution provided by the embodiments of the present invention is feasible and effective.

[0051] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope disclosed in the present invention, based on the technical solution and inventive concept of the present invention, shall fall within the scope of protection of the present invention.

Claims

1. A low-communication-cost network converter control method, characterized in that, Includes the following steps: S1. Construct a frequency-voltage-power closed-loop control model and preset the operating parameter range; S2. Real-time collection of local running volume, comparison with the previous broadcast value, calculation of error norm, and combination with exponential decay threshold to form a trigger function to determine whether to trigger a communication event; S3. When a communication event occurs, estimate the system characteristic quantities and the upper bound of the coupling strength based on local measurement results; S4. Dynamically adjust the exponential decay threshold and trigger function parameters based on the stability margin to ensure the lower bound of the event interval; S5. Based on the local droop control, the neighbor node status correction item is superimposed and updated only when the event is triggered, so as to realize the coordinated recovery of frequency and voltage of multiple machines and power distribution. S6. Implement soft / hard limiting on voltage, frequency, and power. When the operating point approaches the over-limit range, increase the communication trigger frequency. After the over-limit is released, return to low communication mode. S7. After the disturbance is eliminated, continue in low communication mode until the next trigger condition is met.

2. The low-communication-cost network converter control method according to claim 1, characterized in that, The frequency-voltage-power closed-loop control model includes: Based on the system's rated frequency, the frequency command is calculated using the primary frequency droop coefficient according to the active power deviation. Based on the system rated voltage, the voltage command is calculated using the voltage droop coefficient according to the reactive power deviation. A low-pass filter is used to extract the average value of active power and reactive power, and it is compared with the frequency command and voltage command to obtain the deviation input to the droop control. The inner loop controls the instantaneous value of the converter's output current, while the outer loop controls the converter's output voltage.

3. The low-communication-cost network converter control method according to claim 1, characterized in that, Step S2 includes the following sub-steps: Acquire local operating parameters, including real-time frequency, bus voltage, active power and reactive power, to form a set of operating parameters; Save the operating parameters from the last external broadcast and calculate the weighted Euclidean norm error between the current operating quantity and the last broadcast value; Calculate the exponential decay threshold value at the current moment based on the preset initial threshold value for event triggering, the minimum allowed threshold value, the attenuation coefficient, and the time interval since the last communication event triggering. Trigger function formation: If the weighted Euclidean norm error is greater than the exponential decay threshold, it is determined to be an event that requires communication, and the current set of operating parameters is immediately broadcast to neighboring nodes and the trigger time is recorded; If the weighted Euclidean norm error is less than or equal to the exponential decay threshold, then remain silent and do not send any data.

4. The low-communication-cost network converter control method according to claim 1, characterized in that, In step S3, when a communication event occurs, a distributed consensus algorithm is used to estimate the system characteristic quantities and the upper bound of coupling strength based on local measurement results. Specifically: Based on the set of operating parameters and droop control parameters obtained from the current sampling, calculate the local linearized state-space model; The maximum real part eigenvalue and condition number are obtained by calculating the closed-loop eigenvalue set of the system matrix locally. When an event is triggered, the maximum real part eigenvalue and the condition number are sent to the directly adjacent node via point-to-point communication. The adjacent node simultaneously sends its eigenvalues. After the two parties exchange them, the maximum consistency algorithm is iterated to obtain the maximum real part eigenvalue and the maximum condition number of the entire network. Based on the maximum real part eigenvalue and the maximum condition number of the entire network, the upper bound of the coupling strength of the system is obtained.

5. The low-communication-cost network converter control method according to claim 4, characterized in that, In step S4, the grid-type converter receives the maximum real part eigenvalue and maximum condition number of the entire network calculated in step S3, and combines them with the dynamic correction event triggering criterion for the upper bound of coupling strength, including: The stability margin coefficient is defined based on the maximum real part eigenvalue of the entire network and a preset stability security threshold. The stability margin coefficient and the threshold for determining whether the margin is sufficient or insufficient are compared to adjust the exponential decay threshold.

6. A low-communication-cost network converter control method according to claim 1, characterized in that, Step S5 includes the following sub-steps: Using the frequency-voltage-power closed-loop control model established in step S1, calculate the frequency command and voltage command respectively; Correction terms for voltage and frequency are constructed based on the state differences between adjacent nodes; Active power and reactive power are allocated proportionally respectively; Overlay the corrections onto the local control baseline: in, , To incorporate the frequency and voltage control commands with distributed correction, , These are the correction gain coefficients for frequency and voltage, respectively. For frequency commands, This is a voltage command.

7. A low-communication-cost network converter control method according to any one of claims 1-6, characterized in that, Step S7 includes: Continuously monitor local workload and the status information of neighboring nodes. If all workloads are within a safe range and the deviation from the reference value is less than the static deviation threshold, it is determined that the disturbance has been eliminated. Once the disturbance is eliminated, the initial threshold for event triggering is restored to the set normal threshold value, the threshold attenuation coefficient is set to a low value, the triggering interval is extended, and communication is only performed when the triggering function of step S2 is triggered. If no event is triggered within a preset time, a health status packet is periodically sent to neighboring nodes.

8. A low-communication-cost network-based converter control system, characterized in that, The system for implementing the method according to any one of claims 1-7 includes the following modules: The local measurement and execution module is used to collect voltage and current signals at the output of the grid-type converter in real time, calculate instantaneous active and reactive power, detect local operating frequency and bus voltage, input the collected operating quantities into the local execution unit, and drive the power conversion unit to perform regulation according to control commands. The event-triggered communication module is used to calculate the deviation norm between the current running volume and the previous broadcast value, generate an exponential decay threshold, determine whether the exponential decay threshold is exceeded and trigger a communication event, and send the current running data to the neighboring node through a point-to-point communication link; The adaptive parameter estimation module is used to calculate the linearized system matrix based on the local operating state and obtain the maximum real part eigenvalue and condition number. It also exchanges information with neighboring nodes to obtain the maximum eigenvalue and condition number of the entire network and estimates the upper bound of the system coupling strength. The trigger parameter update module is used to determine whether the system state needs to increase or decrease the trigger frequency based on the stability margin coefficient, dynamically adjust the initial threshold value and exponential decay coefficient, and set and execute the minimum time interval of the event. The distributed coordination control module is used to calculate frequency and voltage commands based on local power deviation, receive the operating status of neighboring nodes, calculate frequency and voltage correction terms, allocate active and reactive power reference values ​​according to power ratio, and output the corrected control commands to the local measurement and execution module to realize multi-machine collaborative operation. The protection and limiting module is used to monitor frequency, voltage, active power, and reactive power in real time and compare them with preset limits. When the limit is approaching, a soft limiting strategy is executed. When the limit is exceeded, a hard limiting or emergency shutdown strategy is executed. During the over-limit period, the communication trigger frequency is increased, and after the limit is lifted, the low communication mode is restored.

9. A device, characterized in that, The device includes a processor and a memory for storing instructions or computer programs, and the processor for executing the instructions or computer programs in the memory to cause the device to perform the steps of the method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed on the device, cause the device to perform the steps of the method according to any one of claims 1-7.

Images