Virtual synchronous generator parameter adaptive cooperative monitoring method and device

Abstract

The invention discloses a method and a device for adaptively and cooperatively monitoring parameters of a virtual synchronous generator, and relates to the technical field of virtual synchronous generators. Moreover, the difference between the electric power parameters of the power grid side and the operation parameters of the energy storage system connected with the virtual synchronous generator before and after adjustment is monitored, so that the adaptive performance index of the virtual synchronous generator is judged, data sources are diversified, the accuracy of adaptive performance index evaluation of the virtual synchronous generator is improved, and the evaluation efficiency of the virtual synchronous generator is improved. The stability and the dynamic response speed of the power system are guaranteed, the stability of the new energy in the grid connection process is improved, large-scale application of the new energy in the power system is ensured, meanwhile, the virtual synchronous generators of the power system are divided, and the follow-up maintenance and management efficiency of the virtual synchronous generators is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of virtual synchronous generators, and in particular to a method and device for adaptively coordinating monitoring parameters of virtual synchronous generators. Background Art

[0002] With the rapid development of power systems, traditional power systems are gradually transforming towards intelligence and diversification. The large-scale access of new energy sources such as wind power, solar energy and other renewable energy sources has brought new challenges and opportunities to the power system. However, these new power generation methods usually rely on power electronic equipment for grid connection, resulting in a decrease in the overall inertia and damping characteristics of the power system, which in turn affects the dynamic stability and anti-interference ability of the system. In order to solve this problem, virtual synchronous generator technology came into being. The introduction of virtual synchronous generators helps to improve the dynamic performance and stability of the power system. Therefore, it is extremely necessary to monitor the adaptive adjustment of the parameters of virtual synchronous generators.

[0003] Prior art, such as the invention application patent with announcement number: CN115276093B discloses a virtual synchronous generator parameter adaptive control method based on the DDPG algorithm. First, a virtual synchronous generator control model is established. Then, the active power P1, reactive power Q1, system frequency f1 and voltage U1 output by the control model are collected to form training data. The intelligent agent is trained in combination with the DDPG algorithm to obtain the optimal control variables of the VSG system under the corresponding state: moment of inertia J and damping coefficient D. After the training is completed, the intelligent agent is packaged. Finally, in actual operation, the output of the intelligent agent is adjusted according to the real-time environmental state, and the frequency response of the system is controlled, thereby improving the system operation performance.

[0004] The prior art, such as the invention application patent with announcement number: CN111446741B, discloses a virtual synchronous generator parameter adaptive method for direct-drive wind power generation. When the virtual synchronous generator strategy is applied to the inverter control of the direct-drive wind power generation system, the control parameters virtual moment of inertia and virtual damping coefficient are fixed, so the control is not flexible enough, which limits the achievement of the goal. In view of this shortcoming, the virtual moment of inertia and virtual damping coefficient in the algorithm can be adjusted in real time according to the change of system frequency, and finally the rate and amount of change of system frequency during the fluctuation process are reduced, thereby improving the stability of the power generation system.

[0005] Through the study of the above schemes, it can be found that most of the existing technologies analyze the adaptive parameters of virtual synchronous generators, lack monitoring of the differences before and after the adjustment of the parameters of virtual synchronous generators, and pay little attention to the regulation performance of the grid side and the regulation performance of the energy storage system connected to the virtual synchronous generator. It is difficult to judge the adaptive performance indicators of the virtual synchronous generator, reduce the accuracy of the adaptive performance indicator evaluation of the virtual synchronous generator, affect the stability and dynamic response speed of the entire power system, and it is difficult to ensure the stability of new energy in the grid connection process, reduce the large-scale application of new energy in the power system, and at the same time, lack of classification of virtual synchronous generators based on adaptive performance indicators, It is difficult to provide data support for the subsequent monitoring frequency, maintenance frequency and auxiliary control links of virtual synchronous generators, and reduce the efficiency of subsequent maintenance and management of virtual synchronous generators. Summary of the invention

[0006] The purpose of the present invention is to provide a method and device for adaptively coordinating and monitoring parameters of a virtual synchronous generator, which solves the problems existing in the background technology.

[0007] In order to solve the above technical problems, the present invention adopts the following technical solutions: A first aspect of the present invention provides a virtual synchronous generator parameter adaptive collaborative monitoring method, comprising: ST1, collecting the operation data of the power grid side of the power generation system in the current cycle, the operation data of each virtual synchronous generator, and the operation data of each energy storage system;

[0008] ST2. Determine a regulating parameter data set of each virtual synchronous generator based on the operation data of the power generation system on the grid side in the current cycle, the operation data of each virtual synchronous generator, and the operation data of each energy storage system;

[0009] ST3. Based on the adjustment parameter data set of each virtual synchronous generator, each virtual synchronous generator adjusts its own parameters, and obtains the adjusted collected data on the grid side, the collected data of each virtual synchronous generator, and the collected data of each energy storage system;

[0010] ST4. Based on the collected data on the adjusted grid side, the collected data of each virtual synchronous generator, and the collected data of each energy storage system, the adaptive performance index of each virtual synchronous generator is evaluated;

[0011] ST5. Determine a link set of virtual synchronous generators of the power generation system based on the adaptive performance indicators of the parameters of each virtual synchronous generator.

[0012] A second aspect of the present invention provides a device for executing the method for adaptively coordinating and monitoring parameters of virtual synchronous generators according to the present invention, comprising: a data acquisition module for collecting operation data of the power grid side of the power generation system in the current cycle, operation data of each virtual synchronous generator, and operation data of each energy storage system;

[0013] An adaptive parameter confirmation module is used to determine the adjustment parameter data set of each virtual synchronous generator based on the operation data of the power grid side of the power generation system in the current cycle, the operation data of each virtual synchronous generator, and the operation data of each energy storage system;

[0014] A regulation data acquisition module is used to adjust the parameters of each virtual synchronous generator based on the regulation parameter data set of each virtual synchronous generator, and obtain the collected data of the grid side after adjustment, the collected data of each virtual synchronous generator, and the collected data of each energy storage system;

[0015] An adaptive performance evaluation module, used to evaluate the adaptive performance index of each virtual synchronous generator based on the collected data of the adjusted power grid side, the collected data of each virtual synchronous generator, and the collected data of each energy storage system;

[0016] The link set generation module is used to determine the link set of virtual synchronous generators of the power generation system based on the adaptive performance indicators of the parameters of each virtual synchronous generator.

[0017] The beneficial effects of the present invention are: (1) the present invention monitors the differences in the parameters of the virtual synchronous generator before and after adjustment, and monitors the differences in the power parameters on the grid side and the operating parameters of the energy storage system connected to the virtual synchronous generator before and after adjustment, so as to judge the adaptive performance indicators of the virtual synchronous generator. The data sources are more diversified, which improves the accuracy of the evaluation of the adaptive performance indicators of the virtual synchronous generator, ensures the stability and dynamic response speed of the power system, improves the stability of new energy in the grid connection process, and helps to ensure the large-scale application of new energy in the power system.

[0018] (2) The present invention divides the virtual synchronous generators of the power system based on the adaptive performance indicators of the virtual synchronous generators, provides data support for the subsequent increase of the monitoring frequency, maintenance frequency and auxiliary control links of the virtual synchronous generators, and improves the efficiency of the maintenance management of the subsequent virtual synchronous generators. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 The present invention is a flow chart of the method.

[0021] Figure 2It is a schematic diagram of the system structure connection of the present invention. DETAILED DESCRIPTION

[0022] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] Reference Figure 1 As shown, the first aspect of the present invention provides a method for adaptive collaborative monitoring of virtual synchronous generator parameters, including: ST1, collecting the operation data of the power grid side of the power generation system in the current cycle, the operation data of each virtual synchronous generator, and the operation data of each energy storage system;

[0024] It should be noted that each virtual synchronous generator and each energy storage system are in a one-to-one pairing relationship, that is, one virtual synchronous generator is connected to a single energy storage system.

[0025] In a specific embodiment of the present invention, the operation data on the grid side includes characteristic parameters of various electrical parameters;

[0026] It should be noted that the electrical parameters include but are not limited to voltage, current and frequency.

[0027] It should also be noted that the voltage, current, frequency, etc. can be collected by sensors such as voltage transformers and current transformers, which are relatively mature in the existing technology and will not be elaborated here.

[0028] The operation data of each virtual synchronous generator includes characteristic parameters of each control parameter;

[0029] It should be noted that the control parameters include but are not limited to output power, virtual inertia, damping coefficient and frequency droop coefficient.

[0030] It should also be noted that the virtual inertia, damping coefficient and frequency droop coefficient are obtained from the virtual synchronous generator.

[0031] The operating data of each energy storage system includes characteristic parameters of each operating parameter.

[0032] It should be noted that the operating parameters include but are not limited to capacity, response speed, state of charge, charging current, discharging current and voltage, etc. The state of charge is specifically the ratio between the current remaining power of the energy storage system and its total capacity.

[0033] It should also be noted that the state of charge, charging current, discharging current and voltage are obtained through the online monitoring platform of the energy storage system. The online monitoring platform of the energy storage system is a system that integrates data acquisition, processing and analysis functions. It is designed to monitor the operating status of the energy storage system in real time to ensure its safe and stable operation. The platform uses advanced sensor technology and data processing algorithms to achieve accurate monitoring and real-time feedback of various key parameters of the energy storage system.

[0034] ST2. Determine a regulating parameter data set of each virtual synchronous generator based on the operation data of the power generation system on the grid side in the current cycle, the operation data of each virtual synchronous generator, and the operation data of each energy storage system;

[0035] In a specific embodiment of the present invention, the adjustment parameter data set of each virtual synchronous generator is determined by a specific determination method: obtaining the operation data of the power grid side of the power generation system in each historical period of the current monitoring period, the operation data of each virtual synchronous generator, and the operation data of each energy storage system from the data warehouse, and combining the operation data of the power grid side of the power generation system in the current period, the operation data of each virtual synchronous generator, and the operation data of each energy storage system, to determine the fluctuation change rate of each electrical parameter of the power grid side of the power generation system in the current monitoring period, the fluctuation change rate of each control parameter of each virtual synchronous generator, and the fluctuation change rate of each operating parameter of each energy storage system;

[0036] It should be noted that the method for determining the fluctuation change rate of each electrical parameter on the grid side of the power generation system in the current monitoring period, the fluctuation change rate of each control parameter of each virtual synchronous generator, and the fluctuation change rate of each operating parameter of each energy storage system is as follows: the characteristic parameters of each electrical parameter on the grid side of the power generation system in each historical period of the current monitoring period and the characteristic parameters of each electrical parameter on the grid side of the current period are combined to obtain the characteristic parameters of each electrical parameter on the grid side of the power generation system in the current monitoring period, and the standard deviation of each electrical parameter on the grid side of the power generation system in the current monitoring period is calculated by the standard deviation calculation method, which is used as the fluctuation change rate of each electrical parameter on the grid side of the power generation system in the current monitoring period. Similarly, the fluctuation change rate of each control parameter of each virtual synchronous generator and the fluctuation change rate of each operating parameter of each energy storage system are calculated.

[0037] The method for calculating the standard deviation is prior art and will not be described in detail here.

[0038] Obtain reference characteristic parameters of each electrical parameter, reference characteristic parameters of each control parameter and reference characteristic parameters of each operating parameter from the data warehouse, and obtain the deviation of each electrical parameter of the power generation system on the grid side in the current cycle, the deviation of each control parameter of each virtual synchronous generator, and the deviation of each operating parameter of each energy storage system;

[0039] It should be noted that the characteristic parameters of each electrical parameter of the power generation system on the grid side in the current cycle are subtracted from the reference characteristic parameters to obtain the deviation of each electrical parameter of the power generation system on the grid side in the current cycle. Similarly, the deviation of each control parameter of each virtual synchronous generator and the deviation of each operating parameter of each energy storage system are obtained.

[0040] The associated indicators corresponding to the control parameters of the virtual synchronous generator are obtained from the data warehouse, and the adjustment parameters corresponding to the fluctuation change rate ranges and deviation ranges of the control parameters of the virtual synchronous generator are obtained, the adjustment parameters of the control parameters of the virtual synchronous generator are screened and obtained, and the adjustment parameter data sets of the virtual synchronous generators are summarized.

[0041] It should be noted that the various associated indicators corresponding to the various control parameters of the virtual synchronous generator, such as the various associated indicators corresponding to the virtual inertia, include the frequency, impedance in the electrical parameters, the virtual inertia in the control parameters, and the capacity and response speed in the operating parameters; and the various associated indicators corresponding to the frequency droop coefficient include the frequency, load type in the electrical parameters, the frequency droop coefficient in the control parameters, and the state of charge, charging current, discharging current and response speed in the operating parameters.

[0042] It should also be noted that the adjustment parameters of the control parameters of the virtual synchronous generators corresponding to the fluctuation change rate range and deviation range of the associated indicators are specifically determined based on the historical adaptive adjustment data of the virtual synchronous generators and stored in the data warehouse.

[0043] ST3. Based on the adjustment parameter data set of each virtual synchronous generator, each virtual synchronous generator adjusts its own parameters, and obtains the adjusted collected data on the grid side, the collected data of each virtual synchronous generator, and the collected data of each energy storage system;

[0044] In a specific embodiment of the present invention, the collected data on the grid side after adjustment includes the voltage harmonic distortion rate, the current harmonic distortion rate, and the actual adjustment trend diagram of each electrical parameter within the monitoring period;

[0045] It should be noted that the voltage harmonic distortion rate and the current harmonic distortion rate are specifically obtained by using an oscilloscope or a harmonic analyzer to obtain the voltage harmonic distortion rate and the current harmonic distortion rate. The existing technology is relatively mature and will not be elaborated here.

[0046] The collected data of each virtual synchronous generator includes an actual adjustment trend diagram of each control parameter within a monitoring period;

[0047] The collected data of each energy storage system includes input electric energy, stored electric energy, released electric energy, electric energy received on the grid side, the charge state of each energy storage unit, and the actual adjustment trend chart of each operating parameter during the monitoring period.

[0048] It should be noted that the electric energy received by the grid side is obtained based on the smart meter installed on the grid side, and the input electric energy, stored electric energy, released electric energy and the charge state of each energy storage unit are obtained from the online monitoring platform of the energy storage system.

[0049] ST4. Based on the collected data on the adjusted grid side, the collected data of each virtual synchronous generator, and the collected data of each energy storage system, the adaptive performance index of each virtual synchronous generator is evaluated;

[0050] In a specific embodiment of the present invention, the adaptive performance index of each virtual synchronous generator is evaluated by a specific evaluation method: based on the collected data of the adjusted power grid side, the collected data of each virtual synchronous generator, and the collection system of each energy storage system, the adjustment performance index α of the power grid side and the main body adjustment performance index ε of each virtual synchronous generator are evaluated. _m And the regulation performance index η of each energy storage system _m′ , m is the number of each virtual synchronous generator, m=1,2,...,l, l is any integer greater than 2, m' is the number of each energy storage system, m'=1',2',...,l', l' is any integer greater than 2;

[0051] Based on the numbers of each virtual synchronous generator and each energy storage system, the regulation performance index of the energy storage system corresponding to each virtual synchronous generator is obtained, which is recorded as the energy storage regulation performance index η of each virtual synchronous generator. _m ;

[0052] Import the regulation performance indicators of the grid side, the regulation performance indicators of each virtual synchronous generator and the energy storage regulation performance indicators into the adaptive performance indicator evaluation module Output the adaptive performance index of each virtual synchronous generator where τ 1 , τ 2 They are respectively represented as the weight influence factors corresponding to the main body regulation performance index and energy storage regulation performance index in the data warehouse.

[0053] It should be noted that the weight influence factors corresponding to the main body regulation performance index and the energy storage regulation performance index are intended to adjust the importance of the main body regulation performance index and the energy storage regulation performance index to the adaptive performance index. For example, if the importance of the main body regulation performance index to the adaptive performance index is greater than that of the energy storage regulation performance index to the adaptive performance index, then the weight influence factor of the main body regulation performance index is set greater than that of the energy storage regulation performance index, which is specifically uploaded by a technical engineer.

[0054] In a specific embodiment of the present invention, the specific evaluation method for evaluating the regulation performance index of the power grid side is as follows: obtaining an actual adjustment trend diagram of each electrical parameter from the collected data of the adjusted power grid side, obtaining a steady-state value, overshoot, and response time of each electrical parameter, and fitting a straight line of each electrical parameter based on the actual adjustment trend diagram of each electrical parameter to obtain a straight line slope and buffer time of each electrical parameter;

[0055] It should be noted that the steady-state value is a characteristic parameter of the electrical parameter corresponding to the horizontal line that the curve finally approaches, and the overshoot is the part of the curve that exceeds the steady-state value during the rising or falling process. The specific calculation method of the overshoot is: measure the difference between the maximum peak point (for the rising process) or the minimum valley point (for the falling process) on the curve and the steady-state value, and take the percentage of the difference to the steady-state value as the overshoot. The response time of each control parameter is specifically the interval between the start response time point and the steady-state value time point.

[0056] It should also be noted that the steady-state value, overshoot and response time of each electrical parameter can be obtained by using various tools such as MATALAB, Simulink, and LTspice to output the steady-state value, overshoot and response time of each electrical parameter.

[0057] It should be noted again that when fitting the straight line of each electrical parameter based on the actual adjustment trend chart of each electrical parameter, the characteristic parameter of each electrical parameter is used as the first horizontal axis, the steady-state value of each electrical parameter is used as the second horizontal axis, the data points between the first horizontal axis and the second horizontal axis of each electrical parameter are intercepted, and the straight line of each electrical parameter is fitted. The buffer time is the time length between the time point corresponding to the first intersection of the straight line of each electrical parameter after fitting with the first horizontal axis and the time point of starting response.

[0058] Construct the electrical parameter data set on the grid side, and import the voltage harmonic distortion rate U (THD), current harmonic distortion rate I (THD) and motor parameter data set during the monitoring period on the grid side into the regulation performance index evaluation model on the grid side In the output grid side, the regulation performance index α, where β _ib It is represented as the bth data of the ith electrical parameter in the electrical parameter data set on the grid side, β′ _ib is the bth safety data of the i-th electrical parameter in the safety electrical parameter data set on the power grid side stored in the data warehouse, b is the number of the corresponding data of the electrical parameter in the electrical parameter data set, b∈[1,5], i is the number of each electrical parameter, i=1,2,...,n, n is any integer greater than 2.

[0059] It should be noted that the electrical parameter data set on the grid side includes the steady-state value, overshoot, response time, straight-line slope and buffer time of each electrical parameter, and the safety electrical parameter data set on the grid side includes the safe steady-state value range, safe overshoot range, safe response time range, safe straight-line slope range and safe buffer time range of each electrical parameter.

[0060] In a specific embodiment of the present invention, the specific evaluation method of the main regulation performance index of each virtual synchronous generator is as follows: obtaining the actual adjustment trend diagram of each control parameter within the monitoring period from the collected data of each adjusted virtual synchronous generator, obtaining the steady-state value, overshoot, and response time of each control parameter, and fitting the straight line of each control parameter based on the actual adjustment trend diagram of each control parameter to obtain the straight line slope and response time of each control parameter;

[0061] It should be noted that the steady-state value, overshoot, response time, straight-line slope and response time of each control parameter are obtained in the same manner as the steady-state value, overshoot, response time, straight-line slope and response time of each electrical parameter.

[0062] Construct the control parameter data set of each virtual synchronous generator and import the control parameter data set of each virtual synchronous generator into the main regulation performance index evaluation model Output the regulation performance index ε of each virtual synchronous generator _m , χ _mfp is the pth data of the fth control parameter in the control parameter data set of the mth virtual synchronous generator, χ′ _mfp is the safety interval of the pth data of the fth control parameter in the safety control parameter data set of the mth virtual synchronous generator stored in the data warehouse, p is the number of the corresponding data of the control parameter in the electrical parameter data set, p∈[1,5], f is the number of each control parameter, f=1,2,...,t, t is any integer greater than 2.

[0063] It should be noted that the control parameter data set of each virtual synchronous generator includes the steady-state value, overshoot, response time, straight-line slope and buffer time of each control parameter, and the safety control parameter data set of each virtual synchronous generator includes the safe steady-state value interval, safe overshoot interval, safe response time interval, safe straight-line slope interval and safe buffer time interval of each control parameter.

[0064] In a specific embodiment of the present invention, the regulation performance index of each energy storage system is specifically evaluated by: obtaining an actual adjustment trend diagram of each operating parameter from the collected data of each energy storage system, obtaining a steady-state value, overshoot, and response time of each operating parameter, and obtaining a linear slope and response time of each operating parameter;

[0065] Construct the operating parameter data set of each energy storage system, and input the operating parameter data set of each energy storage system and the electric energy Q during the monitoring period _m′0 , stored energy Q _m′1 , release electric energy Q _m′2 , the grid side receives electric energy Q _m′3 and the charge state H of each energy storage unit _m′j Imported into the regulation performance index evaluation model η of the energy storage system _m′ =μ _1m′ *λ 1 +μ _2m′ *λ 2 +μ _3m′ *λ 3 Output the regulation performance index η of each energy storage system _m′ ,in

[0066] In the formula, Q' and Q" represent the allowable loss storage energy and allowable loss transmission energy stored in the data warehouse, respectively, and δ _m′rh is the hth data of the rth operating parameter in the operating parameter data set of the m'th energy storage system, δ′ _m′rh It is represented as the safety interval of the hth data of the rth operating parameter in the safe operating parameter data set of the m'th energy storage system stored in the data warehouse, h is the number of the corresponding data of the operating parameter in the operating parameter data set, h∈[1,5], r is the number of each operating parameter, r=1,2,...,w, w is any integer greater than 2, j is the number of each energy storage unit, j=1,2,...,k, k is any integer greater than 2, λ 1 , 2 , 3 They are respectively represented as the weight influencing factors corresponding to the charging and discharging efficiency evaluation index, the energy storage unit balance evaluation index, and the operating parameter control evaluation index in the data warehouse.

[0067] It should be noted that the weight influence factors corresponding to the charging and discharging efficiency evaluation index, the energy storage unit balance evaluation index, and the operating parameter control evaluation index are intended to adjust the importance of the charging and discharging efficiency evaluation index, the energy storage unit balance evaluation index, and the operating parameter control evaluation index to the evaluation of the regulation performance index of the energy storage system, and are specifically uploaded by technical engineers.

[0068] It should be noted that the μ _1m′ It is expressed as the charging and discharging efficiency evaluation index of the m'th energy storage system, and the μ _2m′ It is expressed as the energy storage unit balance evaluation index of the m'th energy storage system, and the μ _3m′is the operating parameter regulation evaluation index of the m'th energy storage system.

[0069] It should also be noted that the operating parameter data set of each energy storage system includes the steady-state value, overshoot, response time, straight line slope and buffer time of each operating parameter, and the safe operating parameter data set of each energy storage system includes the safe steady-state value interval, safe overshoot interval, safe response time interval, safe straight line slope interval and safe buffer time interval of each operating parameter.

[0070] The present invention not only monitors the differences before and after adjustment of the parameters of the virtual synchronous generator, but also monitors the differences before and after adjustment of the power parameters on the grid side and the operating parameters of the energy storage system connected to the virtual synchronous generator, so as to judge the adaptive performance indicators of the virtual synchronous generator. The data sources are more diversified, which improves the accuracy of the adaptive performance indicator evaluation of the virtual synchronous generator, ensures the stability and dynamic response speed of the power system, improves the stability of new energy in the grid-connected process, and helps to ensure the large-scale application of new energy in the power system.

[0071] ST5. Determine a link set of virtual synchronous generators of the power generation system based on the adaptive performance indicators of the parameters of each virtual synchronous generator.

[0072] In a specific embodiment of the present invention, the specific determination method for determining the virtual synchronous generator link set of the power generation system is as follows: based on the adaptive performance index of each virtual synchronous generator, if Then the virtual synchronous generator is recorded as an element in the link set of virtual synchronous generators of the power generation system. is the first adaptive performance indicator interval stored in the data warehouse;

[0073] like Then the virtual synchronous generator is recorded as an element in the second-category link set of virtual synchronous generators in the power generation system. is the second adaptive performance indicator interval stored in the data warehouse;

[0074] like Then the virtual synchronous generator is recorded as an element in the three-type link set of virtual synchronous generators in the power generation system. is the third adaptive performance indicator interval stored in the data warehouse;

[0075] Each element in the first link set, each element in the second link set and each element in the third link set of the virtual synchronous generator of the power generation system are summarized to determine the link set of the virtual synchronous generator of the power generation system.

[0076] It should be noted that the importance of the first-class link set of the virtual synchronous generators in the power generation system is greater than that of the second-class link set, and the importance of the second-class link set of the virtual synchronous generators in the power generation system is greater than that of the third-class link set. In other words, the adaptive performance of each virtual synchronous generator in the first-class link set of the virtual synchronous generators in the power generation system is better, which can reduce the monitoring frequency of the virtual synchronous generators and reduce the frequency of daily maintenance. The adaptive performance of each virtual synchronous generator in the second-class link set of the virtual synchronous generators in the power generation system is general, which can maintain the current monitoring frequency and daily maintenance frequency of the virtual synchronous generators. The adaptive performance of each virtual synchronous generator in the three-class link set of the virtual synchronous generators in the power generation system is poor. On the one hand, the monitoring frequency of the virtual synchronous generator can be increased, and the frequency of daily maintenance can be increased. On the other hand, an auxiliary control link can be added to the control loop of the virtual synchronous generator to ensure the adaptive performance of the virtual synchronous generator, provide solid data support for the subsequent daily maintenance and monitoring distribution of the virtual synchronous generator, and help reduce the maintenance and management costs of the virtual synchronous generator.

[0077] The present invention divides the virtual synchronous generators of the power system based on the adaptive performance indicators of the virtual synchronous generators, provides data support for the subsequent increase of the monitoring frequency, maintenance frequency and auxiliary control links of the virtual synchronous generators, and improves the efficiency of the maintenance management of the subsequent virtual synchronous generators.

[0078] Reference Figure 2 As shown, the second aspect of the present invention provides a device for executing the virtual synchronous generator parameter adaptive collaborative monitoring method described in the present invention, including: a data acquisition module, an adaptive parameter confirmation module, an adjustment data acquisition module, an adaptive performance evaluation module, a link set generation module and a data warehouse.

[0079] It should be noted that the data acquisition module is connected to the adaptive parameter confirmation module, the adaptive parameter confirmation module is connected to the adjustment data acquisition module, the adjustment data acquisition module is connected to the adaptive performance evaluation module, the adaptive performance evaluation module is connected to the link set generation module, and the data warehouse is respectively connected to the adaptive parameter confirmation module, the adaptive performance evaluation module and the link set generation module.

[0080] The data acquisition module is used to collect the operation data of the power grid side of the power generation system in the current cycle, the operation data of each virtual synchronous generator, and the operation data of each energy storage system;

[0081] The adaptive parameter confirmation module is used to determine the adjustment parameter data set of each virtual synchronous generator based on the operation data of the power grid side of the power generation system in the current cycle, the operation data of each virtual synchronous generator, and the operation data of each energy storage system;

[0082] The adjustment data acquisition module is used to adjust the parameters of each virtual synchronous generator based on the adjustment parameter data set of each virtual synchronous generator, and obtain the adjusted collected data of the power grid side, the collected data of each virtual synchronous generator, and the collected data of each energy storage system;

[0083] The adaptive performance evaluation module is used to evaluate the adaptive performance index of each virtual synchronous generator based on the adjusted collected data on the grid side, the collected data of each virtual synchronous generator, and the collected data of each energy storage system;

[0084] The link set generation module is used to determine the link set of virtual synchronous generators of the power generation system based on the adaptive performance index of each virtual synchronous generator parameter.

[0085] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A method for adaptive collaborative monitoring of virtual synchronous generator parameters, characterized in that: include: ST1. Collect the grid-side operation data of the power generation system in the current cycle, the operation data of each virtual synchronous generator, and the operation data of each energy storage system; ST2. Determine a regulating parameter data set of each virtual synchronous generator based on the operation data of the power generation system on the grid side in the current cycle, the operation data of each virtual synchronous generator, and the operation data of each energy storage system; ST3. Based on the adjustment parameter data set of each virtual synchronous generator, each virtual synchronous generator adjusts its own parameters, and obtains the adjusted collected data on the grid side, the collected data of each virtual synchronous generator, and the collected data of each energy storage system; ST4. Based on the collected data on the adjusted grid side, the collected data of each virtual synchronous generator, and the collected data of each energy storage system, the adaptive performance index of each virtual synchronous generator is evaluated; ST5. Determine a link set of virtual synchronous generators of the power generation system based on the adaptive performance indicators of the parameters of each virtual synchronous generator.

2. A virtual synchronous generator parameter adaptive collaborative monitoring method according to claim 1, characterized in that: The operation data of the power grid side includes characteristic parameters of various electrical parameters; The operation data of each virtual synchronous generator includes characteristic parameters of each control parameter; The operating data of each energy storage system includes characteristic parameters of each operating parameter.

3. A virtual synchronous generator parameter adaptive collaborative monitoring method according to claim 2, characterized in that: The specific determination method of the adjustment parameter data set of each virtual synchronous generator is as follows: Obtain the grid-side operation data of the power generation system in each historical period of the current monitoring period, the operation data of each virtual synchronous generator, and the operation data of each energy storage system from the data warehouse, and determine the fluctuation change rate of each electrical parameter of the grid side of the power generation system in the current monitoring period, the fluctuation change rate of each control parameter of each virtual synchronous generator, and the fluctuation change rate of each operation parameter of each energy storage system in combination with the grid-side operation data of the power generation system in the current period, the operation data of each virtual synchronous generator, and the operation data of each energy storage system; Obtain reference characteristic parameters of each electrical parameter, reference characteristic parameters of each control parameter and reference characteristic parameters of each operating parameter from the data warehouse, and obtain the deviation of each electrical parameter of the power generation system on the grid side in the current cycle, the deviation of each control parameter of each virtual synchronous generator, and the deviation of each operating parameter of each energy storage system; The associated indicators corresponding to the control parameters of the virtual synchronous generator are obtained from the data warehouse, and the adjustment parameters corresponding to the fluctuation change rate ranges and deviation ranges of the control parameters of the virtual synchronous generator are obtained, the adjustment parameters of the control parameters of the virtual synchronous generator are screened and obtained, and the adjustment parameter data sets of the virtual synchronous generators are summarized.

4. A virtual synchronous generator parameter adaptive collaborative monitoring method according to claim 2, characterized in that: The collected data on the adjusted power grid side includes the voltage harmonic distortion rate, the current harmonic distortion rate, and the actual adjustment trend diagram of each electrical parameter within the monitoring period; The collected data of each virtual synchronous generator includes an actual adjustment trend diagram of each control parameter within a monitoring period; The collected data of each energy storage system includes input electric energy, stored electric energy, released electric energy, electric energy received on the grid side, the charge state of each energy storage unit, and the actual adjustment trend chart of each operating parameter during the monitoring period.

5. A virtual synchronous generator parameter adaptive collaborative monitoring method according to claim 4, characterized in that: The specific evaluation method for evaluating the adaptive performance index of each virtual synchronous generator is as follows: Based on the collected data of the adjusted grid side, the collected data of each virtual synchronous generator, and the collection system of each energy storage system, the regulation performance index α of the grid side and the main regulation performance index ε of each virtual synchronous generator are evaluated. _m And the regulation performance index η of each energy storage system _m′ , m is the number of each virtual synchronous generator, m=1,2,...,l, l is any integer greater than 2, m' is the number of each energy storage system, m'=1',2',...,l', l' is any integer greater than 2; Based on the numbers of each virtual synchronous generator and each energy storage system, the regulation performance index of the energy storage system corresponding to each virtual synchronous generator is obtained, which is recorded as the energy storage regulation performance index η of each virtual synchronous generator. _m ; Import the regulation performance index of the grid side, the regulation performance index of each virtual synchronous generator and the energy storage regulation performance index into the adaptive performance index evaluation module θ _m =α*(ε _m *τ1+η _m *τ2), output the adaptive performance index θ of each virtual synchronous generator _m , where τ1 and τ2 represent the weight influence factors corresponding to the main regulation performance index and energy storage regulation performance index in the data warehouse respectively.

6. A virtual synchronous generator parameter adaptive collaborative monitoring method according to claim 5, characterized in that: The specific evaluation method for evaluating the regulation performance index of the power grid side is as follows: Obtaining the actual adjustment trend diagram of each electrical parameter from the collected data on the adjusted power grid side, obtaining the steady-state value, overshoot, and response time of each electrical parameter, and fitting the straight line of each electrical parameter based on the actual adjustment trend diagram of each electrical parameter to obtain the straight line slope and buffer time of each electrical parameter; Construct the electrical parameter data set on the grid side, and import the voltage harmonic distortion rate U (THD), current harmonic distortion rate I (THD) and motor parameter data set during the monitoring period on the grid side into the regulation performance index evaluation model on the grid side In the output grid side, the regulation performance index α, where β _ib It is represented as the bth data of the ith electrical parameter in the electrical parameter data set on the grid side, β′ _ib is the bth safety data of the i-th electrical parameter in the safety electrical parameter data set on the power grid side stored in the data warehouse, b is the number of the corresponding data of the electrical parameter in the electrical parameter data set, b∈[1,5], i is the number of each electrical parameter, i=1,2,...,n, n is any integer greater than 2.

7. A virtual synchronous generator parameter adaptive collaborative monitoring method according to claim 5, characterized in that: The specific evaluation method of the main regulation performance index of each virtual synchronous generator is as follows: Obtaining an actual adjustment trend diagram of each control parameter within a monitoring period from the collected data of each adjusted virtual synchronous generator, obtaining a steady-state value, overshoot, and response time of each control parameter, and fitting a straight line of each control parameter based on the actual adjustment trend diagram of each control parameter to obtain a straight line slope and response time of each control parameter; Construct the control parameter data set of each virtual synchronous generator and import the control parameter data set of each virtual synchronous generator into the main regulation performance index evaluation model Output the regulation performance index ε of each virtual synchronous generator _m , χ _mfp is the pth data of the fth control parameter in the control parameter data set of the mth virtual synchronous generator, χ′ _mfp is the safety interval of the pth data of the fth control parameter in the safety control parameter data set of the mth virtual synchronous generator stored in the data warehouse, p is the number of the corresponding data of the control parameter in the electrical parameter data set, p∈[1,5], f is the number of each control parameter, f=1,2,...,t, t is any integer greater than 2.

8. A virtual synchronous generator parameter adaptive collaborative monitoring method according to claim 5, characterized in that: The specific evaluation method of the regulation performance index of each energy storage system is as follows: Obtain the actual adjustment trend diagram of each operating parameter from the collected data of each energy storage system, obtain the steady-state value, overshoot, response time of each operating parameter, and obtain the linear slope and response time of each operating parameter; Construct the operating parameter data set of each energy storage system, and input the operating parameter data set of each energy storage system and the electric energy Q during the monitoring period _m′0 , stored energy Q _m′1 , release electric energy Q _m′2 , the grid side receives electric energy Q _m′3 and the charge state H of each energy storage unit _m′j Imported into the regulation performance index evaluation model η of the energy storage system _m′ =μ _1m′ *λ1+μ _2m′ *λ2+μ _3m′ * In λ3, the regulation performance index η of each energy storage system is output _m′ ,in In the formula, Q' and Q" represent the allowable loss storage energy and allowable loss transmission energy stored in the data warehouse, respectively, and δ _m′rh is the hth data of the rth operating parameter in the operating parameter data set of the m'th energy storage system, δ′ _m′rh It is represented as the safety interval of the hth data of the rth operating parameter in the safe operating parameter data set of the m'th energy storage system stored in the data warehouse, h is the number of the corresponding data of the operating parameter in the operating parameter data set, h∈[1,5], r is the number of each operating parameter, r=1,2,...,w, w is any integer greater than 2, j is the number of each energy storage unit, j=1,2,...,k, k is any integer greater than 2, λ1, λ2, λ3 respectively represent the weight influence factors corresponding to the charging and discharging efficiency evaluation index, energy storage unit balance evaluation index, and operating parameter control evaluation index in the data warehouse.

9. A virtual synchronous generator parameter adaptive collaborative monitoring method according to claim 1, characterized in that: The specific method for determining the virtual synchronous generator link set of the power generation system is as follows: Based on the adaptive performance indicators of each virtual synchronous generator, if Then the virtual synchronous generator is recorded as an element in the link set of virtual synchronous generators of the power generation system. is the first adaptive performance indicator interval stored in the data warehouse; like Then the virtual synchronous generator is recorded as an element in the second-category link set of virtual synchronous generators in the power generation system. is the second adaptive performance indicator interval stored in the data warehouse; like Then the virtual synchronous generator is recorded as an element in the three-type link set of virtual synchronous generators in the power generation system. is the third adaptive performance indicator interval stored in the data warehouse; Each element in the first link set, each element in the second link set and each element in the third link set of the virtual synchronous generator of the power generation system are summarized to determine the link set of the virtual synchronous generator of the power generation system.

10. A device for executing the method for adaptive collaborative monitoring of virtual synchronous generator parameters according to any one of claims 1 to 9, characterized in that: include A data acquisition module is used to collect the operation data of the power generation system on the grid side in the current cycle, the operation data of each virtual synchronous generator, and the operation data of each energy storage system; An adaptive parameter confirmation module is used to determine the adjustment parameter data set of each virtual synchronous generator based on the operation data of the power grid side of the power generation system in the current cycle, the operation data of each virtual synchronous generator, and the operation data of each energy storage system; A regulation data acquisition module is used to adjust the parameters of each virtual synchronous generator based on the regulation parameter data set of each virtual synchronous generator, and obtain the collected data of the grid side after adjustment, the collected data of each virtual synchronous generator, and the collected data of each energy storage system; An adaptive performance evaluation module, used to evaluate the adaptive performance index of each virtual synchronous generator based on the collected data of the adjusted power grid side, the collected data of each virtual synchronous generator, and the collected data of each energy storage system; The link set generation module is used to determine the link set of virtual synchronous generators of the power generation system based on the adaptive performance indicators of the parameters of each virtual synchronous generator.

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