Photovoltaic inverter equivalence simplification method based on virtual synchronous machine

Abstract

The invention discloses a photovoltaic inverter equivalence simplification method based on a virtual synchronous machine, and relates to the technical field of inverters, and the method comprises the following steps: Step 1, providing an inverter coherence criterion based on virtual synchronous generator control according to a coherence discrimination method of a synchronous generator in an AC power grid; step 2, carrying out grouping operation on the photovoltaic inverters; and Step 3, according to a coherent equivalence theory in a large power grid, providing a parameter aggregation method of the photovoltaic inverters, and aggregating the photovoltaic inverters in the same group into an equivalent inverter. According to the photovoltaic cluster inverter based on the virtual synchronous generator control strategy, in the process of referring to the large power grid coherence equivalence theory, the judgment criterion of the coherence of the photovoltaic inverter is clarified, and then the equivalent modeling method of the inverter in the electromagnetic transient analysis process is researched. The method solves the problem that the existing photovoltaic system modeling has no corresponding solution measures on the problems of grouping index selection, system parameter aggregation, equivalent model establishment and the like, and the equivalent precision is not enough.

Description

Technical Field

[0001] The present invention relates to the technical field of inverters, and in particular to a photovoltaic inverter equivalent simplification method based on a virtual synchronous machine. Background Art

[0002] In traditional AC systems, there have been a lot of research results on the equivalence of synchronous generator sets, among which the equivalence theory based on coherence has been widely used. In the photovoltaic cluster grid-connected power generation system, when the system operating state changes, the photovoltaic cluster grid-connected power generation system will have complex interactions with the power grid. Therefore, in order to meet the needs of large-scale application of photovoltaic power generation systems, the use of equivalent modeling methods to study the detailed model of photovoltaic clusters using equivalent models has very important research value and significance for efficiently analyzing the interaction between photovoltaic clusters and power systems and the safe and stable operation of power systems. In related fields, existing research is mostly based on grid-following control strategies. In addition, there is still room for optimization in the selection of clustering indicators, system parameter aggregation, and the establishment of equivalent models, and the accuracy of equivalents needs to be improved.

[0003] The paper "Dynamic Clustering Modeling of Regional Centralized Photovoltaic Power Generation System Based on Improved Fuzzy C-means Clustering Algorithm" takes photovoltaic inverters as the core and proposes a dynamic clustering modeling method for regional centralized photovoltaic power generation systems. This method uses the photovoltaic inverter control parameter vector and its sensitivity coefficient to the output trajectory as clustering indicators, and has made certain improvements and innovations in the clustering method; the paper "Research and Application of Equivalent Modeling of Typical Grid-connected Photovoltaic Power Stations" calculates the sensitivity of inverter parameters, obtains the characteristic distance between each inverter and uses this as the equivalence criterion. The equivalent model obtained by this method is difficult to accurately reflect the detailed model; the paper "Coherence Equivalence Method of Grid-connected Inverters and Its Dynamic Analysis Application" proposes a coherence judgment standard based on the generalized Hamiltonian action for grid-connected inverters with multiple state variables, and conducts analysis and experiments on inverters adopting grid-following control strategies.

[0004] In summary, existing research is mostly based on network-following control strategies. In addition, there is still room for optimization in issues such as grouping indicator selection, system parameter aggregation, and equivalent model establishment, and the equivalent accuracy needs to be improved. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a photovoltaic inverter equivalent simplification method based on a virtual synchronous machine. For the photovoltaic inverter based on the virtual synchronous generator control strategy, the judgment criteria for the synchronization of the photovoltaic inverter are clarified by referring to the synchronization equivalent theory of the large power grid, and then the equivalent modeling method of the inverter in the electromagnetic transient analysis process is studied.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is: A photovoltaic inverter equivalent simplification method based on a virtual synchronous machine includes the following steps: Step 1. According to the synchronization judgment method of synchronous generators in AC power grid, an inverter synchronization judgment criterion based on virtual synchronous generator control is proposed; Step 2: Perform grouping operations on photovoltaic cluster inverters; Step 3. Based on the coherent equivalence theory in large power grids, a parameter aggregation method for photovoltaic inverters is proposed to aggregate photovoltaic inverters in the same group into an equivalent inverter.

[0007] The above-mentioned Step 1 inverter synchronization criterion is extracted from the inverter power angle dynamic characteristic curve; after the PV inverter grid-connected system disturbance occurs, the characteristic point is extracted As the clustering indicator, for and difference, is the disturbance occurrence time, It is the moment when the power angle dynamic characteristic curve reaches the first swing peak, indicating the time when the power angle dynamic characteristic curve reaches the first swing peak after the disturbance occurs. for and difference, is the power angle of the photovoltaic grid-connected inverter when the system is running stably before the disturbance occurs, It is the power angle of the first swing peak value on the power angle dynamic characteristic curve, indicating the first swing peak value of the power angle dynamic characteristic curve after the disturbance occurs.

[0008] The above Step 2 clustering adopts the coherent inverter clustering method based on the K-means algorithm, and its specific steps are as follows: Step 2.1, extract the clustering index vector of all inverters in the detailed model; the detailed model is the actual photovoltaic inverter grid-connected system before the equivalent, and the photovoltaic inverter grid-connected system obtained after the equivalent is the equivalent model; Step 2.2, select the initial cluster center and perform preliminary grouping; Step 2.3, calculate the objective function value; calculate the Euclidean distance between each clustering index and the initial clustering center and sum them as the objective function; Step 2.4, update the cluster center and divide the clusters again; Step 2.5, repeat Step 2.3 and Step 2.4 until the change value of the K-means objective function between the two iterations is less than the allowed value, and the iteration ends.

[0009] In the above Step 2, the K-means algorithm is used to cluster the inverters in the photovoltaic cluster, and the following is obtained: K The clustering results of the cluster centers and the inverters of each photovoltaic power generation unit in the photovoltaic cluster are K is an integer.

[0010] In the above Step 3, the photovoltaic cluster structure is obtained from the clustering results obtained in Step 2, which includes c Equivalent photovoltaic system, assuming An equivalent photovoltaic system is The original photovoltaic systems are combined to obtain, 1≤ x ≤ c , the calculation method of equivalent parameters is as follows, so that all c Parameters of an equivalent photovoltaic system: Step 3.1. Before calculating equivalent parameters, make constraints and assumptions; Step 3.2, divide the inverter parameter aggregation into two links: control parameter aggregation and circuit parameter aggregation; Step 3.3, calculate the virtual rotor motion equation; Step 3.4, according to the theory of coherent equivalence, the synchronous generator is equivalenced, and the parameter aggregation in Step 3.2 is used for superposition to obtain the rotor motion equation when the synchronous generator speed is equal; Step 3.5, according to the equal value constraint conditions, perform superposition of control parameter aggregation; Step 3.6. n The synchronous inverters are connected to the same bus, and an equivalent model is established based on the aggregation of inverter LC filter and output line parameters.

[0011] The constraints and assumptions in Step 3.1 above include: Step3.1.1, the voltage of the equivalent model and the detailed model at the PCC grid connection point is the same; Step 3.1.2, the rated capacity of the equivalent model is the same as that of the detailed model, that is: (2); In the formula is the rated capacity of the equivalent model, is the rated capacity of each photovoltaic power generation unit in the detailed model, n is the number of synchronous inverters; Step 3.1.3, the active power output of the equivalent model and the detailed model at the PCC grid connection point is equal, that is: (3); In the formula is the rated active power of the equivalent model, is the rated active power of each photovoltaic power generation unit in the detailed model; Step 3.1.4, the reactive power output of the equivalent model and the detailed model at the PCC grid connection point is equal, that is: (4); In the formula is the rated reactive power of the equivalent model, is the rated reactive power of each photovoltaic power generation unit in the detailed model; Step 3.1.5, the control parameters and circuit parameters in the detailed model can be aggregated separately.

[0012] The specific steps of Step 3.3 above are: The virtual rotor motion equation of the inverter based on the virtual synchronous generator control strategy is: (5); For the photovoltaic cluster The virtual rotor motion equation of an inverter can be expressed as: (6) ; Where: represents the mechanical torque, Indicates The mechanical torque of the inverter, represents the electromagnetic torque, Indicates The electromagnetic torque of the inverter, Indicates The moment of inertia of a virtual synchronous generator, is the generator mechanical angular velocity, is the damping coefficient, Indicates The damping coefficient of the inverter is Indicates The synchronous angular velocity of the generator of each inverter, is the synchronous angular velocity of the generator.

[0013] The rotor motion equation in the above Step 3.4 is: (7); Compared with the virtual rotor motion equation of the inverter based on the virtual synchronous generator control strategy, according to the coherence equivalence theory in the traditional AC system, the control parameter aggregation method in the inverter control system is shown in Equation (8) and Equation (9): (8); (9) ; Where: represents the rotor moment of inertia of the equivalent virtual synchronous generator, Indicates The moment of inertia of a virtual synchronous generator, represents the damping coefficient of the equivalent virtual synchronous generator, Indicates The damping coefficient of a virtual synchronous generator.

[0014] The specific process of Step 3.5 above is: According to the equivalent constraint requirements, the rated capacity, active power and reactive power of the equivalent model and the detailed model are the same, which is reflected in the control system as the aggregation of active power command value and reactive power command value, as shown in Equation (10) and Equation (11): (10); (11); Where: represents the active power command of the equivalent virtual synchronous generator, Indicates The active power command of the virtual synchronous generator, represents the reactive power command of the equivalent virtual synchronous generator, Indicates Reactive power instructions for virtual synchronous generators.

[0015] In the above Step 3.5, the control parameters also include reactive power voltage droop coefficient and reactive virtual inertia coefficient K , the aggregation process is: Reactive voltage droop coefficient and reactive virtual inertia coefficient K Aggregation is also performed in an overlapping manner, as shown in (12) and (13): (12); (13); Where: represents the reactive virtual inertia coefficient of the equivalent virtual synchronous generator, Indicates The reactive virtual inertia coefficient of a virtual synchronous generator, represents the reactive voltage droop coefficient of the equivalent virtual synchronous generator, Indicates Reactive power and voltage droop coefficient of a virtual synchronous generator.

[0016] The specific steps of Step 3.6 above are: n When the synchronous inverters are connected to the same bus, the aggregation of the inverter LC filter and output line parameters is equivalent to the parallel connection of each component in the circuit, which is represented by the symbol / / , as shown in equations (14) to (16): (14); (15); (16); is the equivalent resistance of the inverter filter, , ··· is the branch resistance of the inverter filter, is the equivalent inductance of the inverter filter, , ··· is the branch inductance of the inverter filter, is the equivalent capacitance of the inverter filter, , ··· is the branch capacitance of the inverter filter.

[0017] The present invention provides a photovoltaic inverter equivalent simplification method based on a virtual synchronous machine. Through the equivalent modeling method, the detailed model of the photovoltaic cluster is studied using an equivalent model. It has very important research value and significance for efficiently analyzing the interaction between the photovoltaic cluster and the power system and the safe and stable operation of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The present invention will be further described below in conjunction with the accompanying drawings and embodiments: Figure 1 This is a model diagram of a bipolar photovoltaic power generation unit; Figure 2 This is a structural diagram of a grid-connected inverter system based on virtual synchronous generator control; Figure 3 It is a schematic diagram of the coherence equivalence process of the AC system; Figure 4 This is a typical schematic diagram of the inverter power angle dynamic characteristic curve; Figure 5 It is a schematic diagram of the photovoltaic cluster structure after clustering; Figure 6 yes n Schematic diagram of the circuit structure in which two synchronous inverters are connected to the same bus; Figure 7 It is a schematic diagram of the dynamic response curve of active power to fault disturbance; Figure 8 It is a schematic diagram of the dynamic response curve of reactive power to fault disturbance; Fig. 9 It is a schematic diagram of the dynamic response curve of the output voltage to fault disturbance; Fig.10 It is a schematic diagram of the dynamic response curve of the output current to fault disturbance. DETAILED DESCRIPTION

[0019] The technical solution of the present invention is described in detail below in conjunction with the accompanying drawings and embodiments.

[0020] Example: As the basis of photovoltaic clusters, photovoltaic power generation units mainly include single-stage and bipolar types. A bipolar photovoltaic power generation unit model is as follows: Figure 1 shown by Figure 1 It can be seen that the bipolar photovoltaic power generation unit model is mainly composed of photovoltaic array, DC / DC and its control module, DC / AC and its control module, filter and power grid; among them, the photovoltaic array and DC / DC and its control module can be equivalent to a DC source with constant voltage.

[0021] When the inverter and output line impedance are taken into account, the grid-connected inverter system structure based on virtual synchronous generator control is as follows Figure 2 As shown, the DC source is connected to the power grid after passing through the three-phase full-bridge inverter module, the LC filter and the output line, and its working process is carried out under the constraints of the virtual synchronous generator control algorithm and the voltage and current control loop; wherein, the DC source is equivalent to the prime mover of the virtual synchronous generator, which is used to provide energy, and the three-phase full-bridge inverter and the LC filter are equivalent to the virtual synchronous generator, which are used to realize energy conversion.

[0022] With the large-scale development of photovoltaic power generation, the number of photovoltaic arrays and inverters in photovoltaic clusters continues to increase. A large number of power electronic inverters make the power grid show high-order nonlinear characteristics to the outside world. At the same time, for regional distributed photovoltaic clusters, the parameters of each photovoltaic power generation unit are not exactly the same, so there are certain differences in dynamic characteristics. In this case, when the dynamic characteristics of different photovoltaic power generation units are quite different, using a single-machine equivalent model to equate the detailed model to a photovoltaic power generation system will produce a large error, and then the detailed model cannot be accurately characterized. However, if each photovoltaic power generation unit in the system is modeled, it will cause the problem of a very large model scale. Therefore, it is necessary to take into account the accuracy and simplification of the photovoltaic cluster equivalent model, and establish an equivalent model with sufficient simplification and standard accuracy.

[0023] The coherence equivalence process of the traditional AC system includes: (1) Divide the generator side area and the grid side area, retain the grid side area in the equalization process, and simplify the generator side area; (2) Determine the synchronous generator group in the generator side area; (3) Merge the generator buses in the synchronization group; (4) Simplify the network; (5) Aggregate the homology group parameters to obtain equivalent machine parameters.

[0024] Its principle is as follows Figure 3 shown.

[0025] Based on the synchronous generator characteristics of the photovoltaic inverter using the virtual synchronous generator control strategy, the synchronization identification method of the synchronous generator in the AC system is considered to be used for reference, the power grid containing the photovoltaic inverter is locally equivalent, the network structure is simplified, the system simulation efficiency is improved, and the analysis process of the system is simplified.

[0026] Based on the idea of ​​synchronous equivalence in the dynamic equivalence of power systems, the inverter equivalence method studied takes the inverters with similar dynamic characteristics as the grouping principle, and uses the K-means clustering algorithm to group the inverters so that the inverters in the same group have similar dynamic characteristics. The inverters in the same group are merged into an equivalent inverter to form an equivalent model of regional distributed photovoltaic inverters. The specific process is basically the same as the synchronous equivalence steps of the AC system.

[0027] Although the photovoltaic inverter based on the virtual synchronous generator control strategy has the characteristics of a generator, and the inverter also has an observable power angle after the external system is disturbed, there are still certain differences between the power electronic inverter and the synchronous generator. Therefore, certain corrections need to be made in the equivalent process. The specific problems that need to be solved include: ① Find the clustering index that can represent the dynamic characteristics of the inverter based on the synchronous machine control strategy; ②Choose a suitable clustering algorithm; ③ Based on clustering indicators, use clustering algorithms to group inverters; ④ Parameter calculation of equivalent inverter.

[0028] The existing practical criteria for synchronous generator groups believe that in a given time period The two generators have initial power angles of and , if you use and The maximum absolute value of the difference between the two generators reflects the degree of synchronization between the two generators. When the calculated result is less than the given value When , it satisfies: (1) ; These generators are said to be coherent.

[0029] Generally take , .

[0030] However, there are many factors that affect the dynamic characteristics of photovoltaic inverters, including inverter circuit parameters, inverter control loop parameters and disturbance types, so it is difficult to construct an equivalent criterion that can represent its dynamic characteristics from the inherent parameters of photovoltaic inverters.

[0031] Since there are still essential differences between the power electronic inverter based on the virtual synchronous generator control strategy and the synchronous generator, completely copying and directly applying the synchronization criteria of the synchronous generator will lead to errors in the synchronization inverter judgment, thus affecting the equivalence accuracy; however, after the power electronic inverter is implanted with the torque equation of the synchronous generator, the correspondence between the inverter and the synchronous generator can be used as a reference to a certain extent when selecting the synchronization criteria.

[0032] Considering that the power electronic inverter based on the virtual synchronous machine control strategy has a shorter transient process and can enter the steady state faster after being disturbed by the system, the characteristic points are extracted after the system disturbance occurs. As the clustering indicator, for and The difference between the power angle and the power angle indicates the time when the power angle dynamic characteristic curve reaches the first swing peak after the disturbance occurs. for and The difference between the two represents the first swing peak value of the power angle dynamic characteristic curve after the disturbance occurs. The typical inverter power angle dynamic characteristic curve is as follows: Figure 4 shown.

[0033] Based on the above main ideas of coherence equivalence, coherence equivalence criteria and the principle of K-means algorithm, a coherence inverter clustering method based on K-means algorithm is summarized. The specific steps are as follows: S1: Extract clustering index vectors of all inverters in the detailed model; S2: Select the initial cluster center and perform preliminary grouping; S3: Calculate the objective function value; S4: Update the cluster center and divide the clusters again; by taking the derivative of the input parameters with respect to the objective function, we can obtain the cluster center constraint and the membership function constraint that minimize the objective function. We use the initial cluster center to calculate the membership, and then use the membership to update the cluster center, so as to iterate continuously; S5: Repeat S3 and S4 until the change in the K-means objective function between the two iterations is less than the allowed value, and the iteration ends.

[0034] Using the K-means algorithm to cluster the inverters in the photovoltaic cluster, we can get Cluster centers and clustering results of each photovoltaic power generation unit.

[0035] According to the above method, the inverters in the regional distributed photovoltaic cluster are clustered and divided into groups. The photovoltaic cluster structure obtained after clustering is as follows: Figure 5 shown.

[0036] Theoretically, according to Figure 5 The equivalent model is modeled based on the clustering results, and the obtained equivalent model is basically consistent with the external characteristics of the power grid at the PCC node of the power grid, including power characteristics, frequency characteristics, power angle characteristics, voltage characteristics and current characteristics.

[0037] exist Figure 5 In the As an example, let An equivalent photovoltaic system is The original photovoltaic system is combined and the calculation method of its equivalent parameters is as follows, so we can get Figure 5 All Parameters of an equivalent photovoltaic system.

[0038] Before calculating the equivalent parameters, the following constraints and assumptions are made: ① The voltage of the equivalent model and the detailed model at the PCC grid connection point is the same; ② The rated capacity of the equivalent model is the same as that of the detailed model, that is: (2) ; ③ The active power output of the equivalent model and the detailed model at the PCC grid connection point is equal, that is: (3) ; ④ The reactive power output of the equivalent model and the detailed model at the PCC grid connection point is equal, that is: (4) ; ⑤The control parameters and circuit parameters in the detailed model can be aggregated separately.

[0039] Therefore, inverter parameter aggregation can be divided into two links: control parameter aggregation and circuit parameter aggregation.

[0040] The virtual rotor motion equation of the inverter based on the virtual synchronous generator control strategy is: (5) ; For the photovoltaic cluster The virtual rotor motion equation of an inverter can be expressed as: (6) ; Where: represents the mechanical torque, Indicates The mechanical torque of the inverter, represents the electromagnetic torque, Indicates The electromagnetic torque of the inverter, Indicates The moment of inertia of a virtual synchronous generator, is the generator mechanical angular velocity, is the damping coefficient, Indicates The damping coefficient of the inverter is Indicates The synchronous angular velocity of the generator of each inverter, is the synchronous angular velocity of the generator.

[0041] In traditional AC systems, according to the theory of coherent equivalence, when performing equivalence on synchronous generators, the aggregation of the parameters in the rotor motion equation is achieved by superposition. When the speeds of synchronous generators are equal, it can be expressed as: (7) ; Compared with the virtual rotor motion equation of the inverter based on the virtual synchronous generator control strategy, and drawing on the coherence equivalence theory in the traditional AC system, the control parameter aggregation method in the inverter control system is shown in Equation (8) and Equation (9): (8) ; (9) ; According to the equivalent constraint requirements, the rated capacity, active power and reactive power of the equivalent model and the detailed model are the same, which is reflected in the control system as the aggregation of active power command value and reactive power command value, as shown in Equation (10) and Equation (11): (10) ; (11) ; Other control parameters are also aggregated in a superposition manner, as shown in (12) and (13): (12) ; (13) ; n The circuit structure of two synchronous inverters connected to the same bus is as follows: Figure 6As shown; the aggregation of the inverter LC filter and output line parameters can be regarded as the parallel equivalent of each component in the circuit, represented by the symbol / / , as shown in equations (14) to (16).

[0042] (14) ; (15) ; (16) ; is the equivalent resistance of the inverter filter, , ··· is the branch resistance of the inverter filter, is the equivalent inductance of the inverter filter, , ··· is the branch inductance of the inverter filter, is the equivalent capacitance of the inverter filter, , ··· is the branch capacitance of the inverter filter.

[0043] Theoretically, an equivalent model is established according to the above-mentioned equivalent modeling method, which is basically consistent with the external characteristics of the detailed model on the power grid at the PCC node of the power grid, including power characteristics, frequency characteristics, power angle characteristics, voltage characteristics and current characteristics.

[0044] In order to verify the feasibility and accuracy of the proposed equivalent simplification method for photovoltaic inverters based on virtual synchronous machines, a multi-inverter parallel simulation platform based on virtual synchronous machine control strategy was built in the Matlab / Simulink simulation environment. The simulation platform includes 5 grid-connected inverters with different parameters based on virtual synchronous generator control, which are connected in parallel and run on the same AC bus. During the modeling process, the inverter side area is equivalently simplified, while the grid side area is kept unchanged.

[0045] During the case analysis process, the clustering indicators in the power angle curves of each inverter are extracted to determine the coherence between the inverters and divide them into cluster groups, and then the parameter aggregation is completed to obtain the inverter multi-machine equivalent model; finally, a simulated disturbance is applied to the grid-connected system, and the dynamic response curves of the detailed model and the equivalent model are compared and analyzed, and then the efficiency and accuracy of the equivalent model are calculated.

[0046] During the simulation, a fault disturbance is set to compare the dynamic response curves of active power, reactive power, output voltage and output current at the boundary line B between the inverter side area and the grid side area before and after the equalization. The results are as follows: Figure 7~Figure 10 shown.

[0047] Depend on Figure 7 and Figure 8 It can be seen that after a single-phase ground short-circuit fault occurs in the system, the active power and reactive power drop briefly, then rise rapidly to provide frequency and voltage support, and then enter an oscillation state and gradually tend to stabilize; the system detailed model and the equivalent model are simulated and analyzed respectively, and the dynamic response curve data of active power and reactive power are extracted, the simulation results of the two models are compared and calculated: the maximum error of the active power transient process is 6.45%; the maximum error of the reactive power transient process is 3.85%.

[0048] exist Fig. 9 and Fig.10 In the paper, by extracting the dynamic response curve data of output voltage and output current, comparing the simulation results of the two models and calculating, it is found that the maximum error of the output voltage transient process is 5.13%; the maximum error of the output current transient process is 1.01%.

[0049] Figure 7-Figure 10 The corresponding data table is as follows: Table 1 Comparison of fault disturbance active power, reactive power, voltage and current dynamic response data

[0050] From the above analysis, it can be seen that no matter the active power, reactive power, output voltage or output current dynamic response curve of the equivalent model, its similarity with the dynamic response curve of the detailed model is very high. Compared with the detailed model, the equivalent error is very small, which is within the acceptable error range of power grid analysis.

[0051] As mentioned above, one of the purposes of constructing an inverter equivalent model is to improve the efficiency of system analysis. This paper uses the simulation time required for the detailed model and the equivalent model to reflect the analysis efficiency, as shown in Table 2.

[0052] Table 2 Time required for model simulation

[0053] It can be seen from Table 1 that under the same operating conditions, the detailed model takes 108 seconds to complete the simulation, while the equivalent model only takes 38 seconds to complete the simulation. Compared with the detailed model, the simulation efficiency of the equivalent model is improved by 184%. The example only calculates the equivalent model of 5 inverters. When the number of inverters increases, the difference in simulation time required for the detailed model and the equivalent model will be even greater. At the same time, the significance of building an equivalent model of the inverter will become more significant.

[0054] This paper establishes an equivalent model and performs simulation for a simplification method for photovoltaic inverter equivalents based on virtual synchronous machines, illustrating that the proposed synchronization criteria and grouping algorithm suitable for power electronic inverters fully consider the operating conditions of the inverter, making the identification of the inverter synchronization group more accurate; the power electronic inverter parameter aggregation method designed in combination with the synchronous generator parameter aggregation process in traditional large power grids is simpler and more feasible than existing methods, and is more suitable for scenarios involving large-scale inverter grid-connected equivalents using virtual synchronous generator control strategies.

Claims

1. A photovoltaic inverter equivalent simplification method based on a virtual synchronous machine, characterized in that: The following steps are involved: Step 1. According to the synchronization judgment method of synchronous generators in AC power grid, an inverter synchronization judgment criterion based on virtual synchronous generator control is proposed; The inverter synchronization criterion is extracted from the dynamic characteristic curve of the inverter power angle; after the PV inverter grid-connected system disturbance occurs, the characteristic points are extracted As the clustering indicator, for and difference, is the disturbance occurrence time, It is the moment when the power angle dynamic characteristic curve reaches the first swing peak, indicating the time when the power angle dynamic characteristic curve reaches the first swing peak after the disturbance occurs. for and difference, is the power angle of the photovoltaic grid-connected inverter when the system is running stably before the disturbance occurs, is the power angle of the first swing peak value on the power angle dynamic characteristic curve, indicating the first swing peak value of the power angle dynamic characteristic curve after the disturbance occurs; Step 2: Perform grouping operations on photovoltaic cluster inverters; Step 3. Based on the coherent equivalence theory in large power grids, a parameter aggregation method for photovoltaic inverters is proposed to aggregate photovoltaic inverters in the same group into an equivalent inverter.

2. A photovoltaic inverter equivalent simplification method based on a virtual synchronous machine according to claim 1, characterized in that: The Step 2 clustering adopts the coherent inverter clustering method based on the K-means algorithm, and its specific steps are as follows: Step 2.1, extract the clustering index vector of all inverters in the detailed model; the detailed model is the actual photovoltaic inverter grid-connected system before the equivalent, and the photovoltaic inverter grid-connected system obtained after the equivalent is the equivalent model; Step 2.2, select the initial cluster center and perform preliminary grouping; Step 2.3, calculate the objective function value; calculate the Euclidean distance between each clustering index and the initial clustering center and sum them as the objective function; Step 2.4, update the cluster center and divide the clusters again; Step 2.5, repeat Step 2.3 and Step 2.4 until the change value of the K-means objective function between the two iterations is less than the allowed value, and the iteration ends.

3. A photovoltaic inverter equivalent simplification method based on a virtual synchronous machine according to claim 2, characterized in that: In Step 2, the K-means algorithm is used to cluster the inverters in the photovoltaic cluster, and the following can be obtained: K The clustering results of the cluster centers and the inverters of each photovoltaic power generation unit in the photovoltaic cluster are K is an integer.

4. The photovoltaic inverter equivalent simplification method based on virtual synchronous machine according to claim 3 is characterized in that: In Step 3, the photovoltaic cluster structure is obtained from the clustering results obtained in Step 2, which includes c Equivalent photovoltaic system, assuming An equivalent photovoltaic system is The original photovoltaic systems are combined to obtain, 1≤ x ≤ c , the calculation method of equivalent parameters is as follows, so that all c Parameters of an equivalent photovoltaic system: Step 3.

1. Before calculating equivalent parameters, make constraints and assumptions; Step 3.2, divide the inverter parameter aggregation into two links: control parameter aggregation and circuit parameter aggregation; Step 3.3, calculate the virtual rotor motion equation; Step 3.4, according to the theory of coherent equivalence, the synchronous generator is equivalenced, and the parameter aggregation in Step 3.2 is used for superposition to obtain the rotor motion equation when the synchronous generator speed is equal; Step 3.5, according to the equal value constraint conditions, perform the superposition of control parameter aggregation; Step 3.

6. n The synchronous inverters are connected to the same bus, and an equivalent model is established based on the aggregation of inverter LC filter and output line parameters.

5. The photovoltaic inverter equivalent simplification method based on virtual synchronous machine according to claim 4, characterized in that: The constraints and assumptions in Step 3.1 include: Step3.1.1, the voltage of the equivalent model and the detailed model at the PCC grid connection point is the same; Step 3.1.2, the rated capacity of the equivalent model is the same as that of the detailed model, that is: (2)； In the formula is the rated capacity of the equivalent model, is the rated capacity of each photovoltaic power generation unit in the detailed model, n is the number of synchronous inverters; Step 3.1.3, the active power output of the equivalent model and the detailed model at the PCC grid connection point is equal, that is: (3)； In the formula is the rated active power of the equivalent model, is the rated active power of each photovoltaic power generation unit in the detailed model; Step 3.1.4, the reactive power output of the equivalent model and the detailed model at the PCC grid connection point is equal, that is: (4)； In the formula is the rated reactive power of the equivalent model, is the rated reactive power of each photovoltaic power generation unit in the detailed model; Step 3.1.5, the control parameters and circuit parameters in the detailed model are aggregated separately.

6. A photovoltaic inverter equivalent simplification method based on a virtual synchronous machine according to claim 5, characterized in that: The specific steps of Step 3.3 are: The virtual rotor motion equation of the inverter based on the virtual synchronous generator control strategy is: (5)； For the photovoltaic cluster The virtual rotor motion equation of an inverter is expressed as: (6) ； Where: represents the mechanical torque, Indicates The mechanical torque of the inverter, represents the electromagnetic torque, Indicates The electromagnetic torque of the inverter, Indicates The moment of inertia of a virtual synchronous generator, is the generator mechanical angular velocity, is the damping coefficient, Indicates The damping coefficient of the inverter is Indicates The synchronous angular velocity of the generator of each inverter, is the synchronous angular velocity of the generator.

7. A photovoltaic inverter equivalent simplification method based on a virtual synchronous machine according to claim 6, characterized in that: The rotor motion equation in Step 3.4 is: (7)； Compared with the virtual rotor motion equation of the inverter based on the virtual synchronous generator control strategy, according to the coherence equivalence theory in the traditional AC system, the control parameter aggregation method in the inverter control system is shown in Equation (8) and Equation (9): (8)； (9) ； Where: represents the rotor moment of inertia of the equivalent virtual synchronous generator, Indicates The moment of inertia of a virtual synchronous generator, represents the damping coefficient of the equivalent virtual synchronous generator, Indicates The damping coefficient of a virtual synchronous generator.

8. The photovoltaic inverter equivalent simplification method based on virtual synchronous machine according to claim 7, characterized in that: The specific process of Step 3.5 is as follows: According to the equivalent constraint requirements, the rated capacity, active power and reactive power of the equivalent model and the detailed model are the same, which is reflected in the control system as the aggregation of active power command value and reactive power command value, as shown in Equation (10) and Equation (11): (10)； (11)； Where: represents the active power command of the equivalent virtual synchronous generator, Indicates The active power command of the virtual synchronous generator, represents the reactive power command of the equivalent virtual synchronous generator, Indicates Reactive power instructions for virtual synchronous generators.

9. A photovoltaic inverter equivalent simplification method based on a virtual synchronous machine according to claim 8, characterized in that: In the above Step 3.5, the control parameters also include reactive voltage droop coefficient and reactive virtual inertia coefficient K , the aggregation process is: Reactive voltage droop coefficient and reactive virtual inertia coefficient K Aggregation is also performed in an overlapping manner, as shown in (12) and (13): (12)； (13)； Where: represents the reactive virtual inertia coefficient of the equivalent virtual synchronous generator, Indicates The reactive virtual inertia coefficient of a virtual synchronous generator, represents the reactive voltage droop coefficient of the equivalent virtual synchronous generator, Indicates Reactive power and voltage droop coefficient of a virtual synchronous generator.

10. A photovoltaic inverter equivalent simplification method based on a virtual synchronous machine according to claim 9, characterized in that: The specific steps of Step 3.6 are: n When the synchronous inverters are connected to the same bus, the aggregation of the inverter LC filter and output line parameters is equivalent to the parallel connection of each component in the circuit, which is represented by the symbol / / , as shown in equations (14) to (16): (14)； (15)； (16)； is the equivalent resistance of the inverter filter, , ··· is the branch resistance of the inverter filter, is the equivalent inductance of the inverter filter, , ··· is the branch inductance of the inverter filter, is the equivalent capacitance of the inverter filter, , ··· is the branch capacitance of the inverter filter.

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