New energy station impedance calculation method

Abstract

The invention is suitable for the technical field of impedance calculation, and provides a new energy station impedance calculation method, which comprises the following steps: inputting acquired broadband impedance characteristic data into a preset clustering algorithm model for clustering analysis, and generating a plurality of unit clusters; calculating an equivalent impedance characteristic of the current cluster, and determining an equivalent frequency domain network equivalent FDNE unit corresponding to the current cluster according to the equivalent impedance characteristic; constructing a function taking maximization of a stability margin and minimization of a harmonic distortion rate as optimization targets, and solving an optimal solution set of the function by taking key parameters of each equivalent FDNE unit of the equivalent frequency domain network as optimization variables; according to the actual electrical topology of the new energy station, the optimized FDNE units are connected, and a full-field equivalent simulation model is constructed; calculating the equivalent impedance characteristic of the grid-connected point of the new energy station through a full-field equivalent simulation model; the calculation efficiency is greatly improved on the premise of ensuring the modeling precision.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of impedance calculation, in particular to a new energy station impedance calculation method. BACKGROUND

[0002] With the continuous expansion of the scale of new energy power generation grid connection, the complex interaction between power electronic devices represented by grid-connected inverters (GCI, Grid-Connected Inverters) and weak power grids has become increasingly prominent, and the wideband oscillation problems such as sub / super synchronous oscillation and harmonic resonance caused by it seriously threaten the safe and stable operation of the system. In order to further improve the new energy consumption rate and improve the power quality of new energy access, stability analysis needs to be carried out on the new energy power system to ensure the safe operation of the power grid. At present, the eigenvalue analysis method based on the state space model faces the problems of complex model construction, poor parameter adaptability and "dimension disaster", and is difficult to be applied to actual large new energy stations. Although the impedance analysis method can avoid the dependence on internal parameters of the equipment through measurement means, when dealing with large new energy stations, due to the large number of units in the station, the complex impedance characteristics and the change with the operating condition, combined with the influence of the electrical topology structure, the traditional simulation method has high dimension and ill-conditioned numerical problems, and it is difficult to realize the fine impedance modeling and stability characteristic analysis of the whole station.

[0003] In view of this, a new energy station impedance calculation method is proposed. SUMMARY

[0004] The present application provides a new energy station impedance calculation method, which is used to solve the problem that the traditional simulation method has high dimension and ill-conditioned numerical problems, and it is difficult to realize the fine impedance modeling and stability characteristic analysis of the whole station.

[0005] The present application provides a new energy station impedance calculation method, which comprises: Obtaining the wideband impedance characteristic data of each new energy unit in the new energy station under different operating conditions; Inputting the wideband impedance characteristic data of each new energy unit into a preset clustering algorithm model for clustering analysis to generate a plurality of unit clusters; Based on the impedance characteristic data of each unit in each unit cluster, the equivalent impedance characteristic of the current cluster is calculated, and the equivalent frequency domain network equivalent FDNE unit corresponding to the current cluster is determined according to the equivalent impedance characteristic; Constructing a function with the optimization objectives of maximizing the stability margin and minimizing the harmonic distortion rate, taking the key parameters of each equivalent frequency domain network equivalent FDNE unit as optimization variables, and solving the optimal solution set of the function; According to the actual electrical topology of the new energy station, the optimized equivalent frequency domain network equivalent FDNE units are connected to construct a full-station equivalent simulation model; Calculate the equivalent impedance characteristics of the new energy station grid-connected point through the full-field equivalent simulation model.

[0006] Further, the wideband impedance characteristic data of each new energy unit is input into a preset clustering algorithm model for clustering analysis to generate a plurality of unit clusters, including: From the wideband impedance characteristic data, the impedance amplitude-frequency curve, impedance phase-frequency curve and resonance frequency point information of each unit are extracted, and the impedance amplitude similarity, impedance phase angle similarity and resonance point distribution similarity between any two new energy units are calculated based on the extracted data information; According to the impedance amplitude similarity, impedance phase angle similarity and resonance point distribution similarity, the comprehensive similarity between the two new energy units is determined; Based on the comprehensive similarity between all pairs of new energy units, an initial unit cluster division is generated; Optimize and verify the initial unit cluster division to generate the final plurality of unit clusters.

[0007] Further, the comprehensive similarity between the two new energy units is determined according to the impedance amplitude similarity, impedance phase angle similarity and resonance point distribution similarity, including: Obtain preset amplitude weight coefficient, phase angle weight coefficient and resonance point weight coefficient; According to the amplitude weight coefficient, phase angle weight coefficient and resonance point weight coefficient, the impedance amplitude similarity, impedance phase angle similarity and resonance point distribution similarity are weighted and summed, and the calculation result is determined as the comprehensive similarity.

[0008] Further, the initial unit cluster division is optimized and verified to generate the final plurality of unit clusters, including: Calculate the clustering evaluation index of each unit cluster in the initial unit cluster division; Determine whether the clustering evaluation index meets the preset qualified threshold; if so, confirm that the initial unit cluster division is the final plurality of unit clusters.

[0009] Further, the determination of whether the clustering evaluation index meets the preset qualified threshold includes: If the clustering evaluation index does not meet the preset qualified threshold, adjust the hyperparameters of the clustering algorithm model; Based on the adjusted hyperparameters, re-execute the clustering analysis; determine whether the clustering evaluation index of the unit cluster division obtained after re-clustering reaches the preset qualified threshold; if yes, confirm that the unit cluster division after re-clustering is the final unit cluster division; if not, iteratively perform the steps of adjusting the hyperparameters and re-clustering until the clustering evaluation index reaches the preset qualified threshold or a maximum number of iterations is reached.

[0010] Further, the calculation of the equivalent impedance characteristic of the current cluster based on the impedance characteristic data of each unit in each unit cluster comprises: obtaining complex impedance data of all new energy units in the current unit cluster under the same frequency sequence; performing parallel equivalent calculation on all complex impedance data under the same frequency sequence respectively to obtain equivalent complex impedance of the current unit cluster at each frequency point; the equivalent impedance characteristic of the current cluster is composed of the equivalent complex impedance at all frequency points.

[0011] Further, the determination of the equivalent frequency domain network equivalent FDNE unit corresponding to the current cluster based on the equivalent impedance characteristic comprises: organizing the frequency sequence in the equivalent impedance characteristic and the real part and imaginary part data of the equivalent complex impedance corresponding to each frequency point in a preset format; importing the organized data into an FDNE model construction interface of a simulation platform; generating an equivalent frequency domain network equivalent FDNE unit representing the current cluster in the simulation platform based on the organized data, the frequency response characteristic of the equivalent frequency domain network equivalent FDNE unit being consistent with the equivalent impedance characteristic.

[0012] Further, the construction of the function with the optimization objectives of maximizing the stability margin and minimizing the total harmonic distortion rate comprises: the expression of the function is as follows: wherein: is an optimization variable vector, the components of which are composed of key parameters of each equivalent FDNE unit, is the system stability margin, is the current total harmonic distortion rate, is a weight coefficient, when is close to 1, the optimization process focuses more on maximizing the stability margin, and when is close to 0, the optimization process focuses more on minimizing the total harmonic distortion rate, To at a specific frequency Phase margin below, , These are the minimum specific frequency and the maximum specific frequency, respectively. For the highest harmonic order considered, The first of the grid-connected current RMS value of subharmonic components This represents the effective value of the fundamental component of the grid-connected current.

[0013] Furthermore, the calculation of the equivalent impedance characteristics of the grid connection point of the new energy power station using the full-field equivalent simulation model includes: A harmonic impedance scanning module is connected at the grid connection point of the new energy power station in the full-field equivalent simulation model. The scanning parameters of the harmonic impedance scanning module are set, including the start frequency, the end frequency, and the frequency interval. Run the full-field equivalent simulation model, inject a small broadband voltage disturbance into the grid connection point through the harmonic impedance scanning module, and measure the current response of the grid connection point; Based on the wideband voltage disturbance and the current response, the equivalent impedance frequency characteristics of the grid connection point of the new energy power station are calculated.

[0014] Furthermore, the broadband voltage perturbation is a harmonic voltage sequence containing multiple frequency components, expressed as: in: For wideband voltage small disturbance, Upper limit of harmonic order For the first Voltage amplitude of each frequency component For the first The frequency value of each frequency component For the first Phase offset of each frequency component Time is the continuously changing independent variable.

[0015] As can be seen from the above technical solutions, the present invention has the following advantages: After the wideband impedance characteristic data of each unit in the field station under different operating conditions are obtained, the units are divided into several clusters according to the impedance characteristic similarity by using a clustering algorithm; the equivalent impedance characteristic of each cluster is calculated, and an equivalent frequency domain network equivalent FDNE unit representing the cluster is constructed; the key parameters of each equivalent FDNE unit are optimized with the maximum stable margin and the minimum harmonic distortion rate as the target; finally, the optimized equivalent FDNE units are connected according to the actual electrical topology, the full-field equivalent simulation model is constructed, and the equivalent impedance characteristic of the field station grid-connected point is calculated through the model. The method effectively solves the calculation problem of large new energy field stations caused by the large number of units, complex characteristics and variable topology structure, realizes the substantial improvement of the calculation efficiency under the premise of ensuring the modeling accuracy, and provides a reliable data basis for the field station level wideband oscillation stability analysis and suppression strategy formulation. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 An embodiment flowchart of a new energy field station impedance calculation method in the application; Figure 2 Another embodiment flowchart of a new energy field station impedance calculation method in the application; Figure 3 Another embodiment flowchart of a new energy field station impedance calculation method in the application; Figure 4 Another embodiment flowchart of a new energy field station impedance calculation method in the application; Figure 5 Another embodiment flowchart of a new energy field station impedance calculation method in the application; Figure 6 A wind farm topology structure diagram of an example scenario in the application; Figure 7 A 500kV voltage FFT analysis result diagram of an on-site land station in the application; Figure 8 A normal board / backup board parameter wind turbine impedance curve comparison diagram in the application; Figure 9 An impedance characteristic diagram of five normal board parameter wind turbine units and one backup board parameter wind turbine unit in the application; Figure 10 An impedance characteristic diagram of only five normal board parameter wind turbine units in the application. DETAILED DESCRIPTION

[0017] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “corresponding to,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0018] Example 1 The implementation method in this embodiment can be implemented in a system, on a server, or on a terminal; no specific limitation is made. The following section will describe the impedance calculation method for new energy power plants in this application from the perspective of system implementation. Please refer to... Figures 1 to 5 The method provided in this application includes the following steps: S1. Obtain broadband impedance characteristic data of each new energy unit in the new energy power station under different operating conditions; Here, each renewable energy unit refers to the smallest collection of power generation equipment in a renewable energy power plant that can operate independently and function as a basic control unit. A unit is a functional unit, not a mechanical unit; its core is the grid-connected inverter and its control system, as impedance characteristics are primarily determined by the inverter's control strategy. A physical "wind turbine" or a "photovoltaic array" constitutes a unit. Different operating conditions refer to the variable internal operating states and external grid conditions that affect the impedance characteristics of renewable energy units. Impedance characteristics are not fixed; therefore, measurements must be taken under various representative operating conditions to comprehensively describe their characteristics.

[0019] The broadband impedance characteristic data mentioned here refers to data that exists in the form of a discrete data point set and can completely describe the impedance variation characteristics of the unit with frequency. The specific implementation method is as follows: 1. Remove the controller of the actual new energy unit from the unit and use it as the hardware part. Use a real-time simulator to simulate the main circuit of the unit and the power grid environment as the loop part. Output the controller's pulse signal to the real-time simulator, and at the same time feed back the grid voltage, current and other signals calculated by the real-time simulator to the controller.

[0020] 2. Set the corresponding power grid conditions in the real-time simulator, such as power grid short-circuit capacity and line impedance; and make the controller run at the specified power point and control mode.

[0021] 3. Superimpose a wideband voltage disturbance signal on the grid voltage in the real-time simulator, where the wideband voltage disturbance signal contains multiple frequency components that can stimulate the response of the unit in a wide frequency range at one time; measure the voltage and current changes at the grid connection point caused by the disturbance at the same time.

[0022] 4. Perform fast Fourier transform on the measured voltage and current signals to decompose them into the frequency domain and obtain the voltage components and the current components at each frequency point According to Ohm's law, calculate the impedance at each frequency point; the impedance value is a complex number containing a real part and an imaginary part.

[0023] 5. Store the data pairs of each frequency point and its corresponding complex impedance value to form a wideband impedance characteristic data set of the unit under the current operating condition.

[0024] 6. Change the operating condition and repeat the above steps to obtain a set of impedance characteristic data sets of the unit under a series of different operating conditions.

[0025] S2. Input the wideband impedance characteristic data of each new energy unit into a preset clustering algorithm model for clustering analysis to generate a number of unit clusters; The preset clustering algorithm model is a calculation framework that uses impedance characteristic similarity as the only measurement standard and can automatically discover the internal grouping structure of the data. Its core is based on the density clustering algorithm and has been adaptively optimized for the characteristics of impedance data (such as complex form, frequency variation characteristics). The discrete data set obtained in step S1 is input into the clustering algorithm model, and the specific implementation is as follows: S211. Extract the impedance amplitude-frequency curve, impedance phase-frequency curve, and resonance frequency point information of each unit from the wideband impedance characteristic data, and calculate the impedance amplitude similarity, impedance phase angle similarity, and resonance point distribution similarity between any two new energy units based on the extracted data information; The curve here refers to a discrete data sequence, which can be obtained directly from the data set obtained in S1. The impedance amplitude sequence and impedance phase angle sequence corresponding to each frequency point are the digital representation of the curve. By scanning the impedance amplitude sequence through the algorithm, the local maximum point is found; the frequency value of this point is the resonance frequency, and the amplitude value of this point is the resonance peak amplitude. A unit may have multiple resonance points, so the resonance frequency point information is a set containing multiple data pairs.

[0026] The impedance amplitude similarity is to calculate the similarity of impedance amplitude sequences of two units under the same frequency sequence. The closer the correlation coefficient is to 1, the more consistent the shape and trend of the two amplitude-frequency curves are. The impedance phase angle similarity is to calculate the Pearson correlation coefficient of impedance phase angle sequences of two units. The resonance point distribution similarity is to first regard the resonance point information of each unit as a set of points in the frequency-amplitude two-dimensional space, and then calculate the Hausdorff distance between the resonance point sets of two units. The smaller the distance is, the more similar the resonance point distribution of the two units is. Finally, the distance is mapped to a similarity value between 0 and 1.

[0027] S212. According to the impedance amplitude similarity, the impedance phase angle similarity and the resonance point distribution similarity, the comprehensive similarity between any two new energy units is determined. 1. Obtain the preset amplitude weight coefficient, phase angle weight coefficient and resonance point weight coefficient. 2. According to the amplitude weight coefficient, the phase angle weight coefficient and the resonance point weight coefficient, the impedance amplitude similarity, the impedance phase angle similarity and the resonance point distribution similarity are weighted and summed, and the calculation result is determined as the comprehensive similarity.

[0028] Before starting the clustering analysis, the system loads a set of pre-defined weight coefficients from the configuration file or the database. These coefficients are not calculated in real time by the algorithm, but are set manually according to prior engineering knowledge and the actual focus of stability analysis, or are obtained by optimizing historical data.

[0029] The amplitude weight coefficient defines the importance of impedance amplitude similarity in comprehensive judgment. If the overall level of impedance amplitude is considered to play a dominant role in stability, it should be given a higher weight. The phase angle weight coefficient defines the importance of impedance phase angle similarity. In the analysis of phase margin related stability problems, this weight will be more prominent. The resonance point weight coefficient defines the importance of resonance point distribution similarity. Resonance points are directly related to the risk position of sub- / super-synchronous oscillation of the system, so they are given a higher weight to ensure that units with similar resonance characteristics are preferentially divided into the same cluster.

[0030] The calculation process is to multiply the impedance amplitude similarity by its importance weight, multiply the impedance phase angle similarity by its importance weight, multiply the resonance point distribution similarity by its importance weight, and add the three products to obtain the comprehensive similarity of the two units. This comprehensive similarity is a scalar value between 0 and 1. The closer the value is to 1, the more similar the overall impedance characteristics of the two units are; the closer to 0, the more dissimilar they are.

[0031] The above-mentioned cluster refers to a set of machine groups, each of which can be an independent equivalent unit. The machine groups in the cluster can be represented by a common equivalent FDNE model, thereby greatly simplifying the complexity of the full-field simulation model under the premise of ensuring accuracy.

[0032] S213. Based on the comprehensive similarity between all new energy machine groups, an initial machine group cluster division is generated; The comprehensive similarity between all machine groups calculated in S212 is composed into a similarity matrix, where N is the total number of machine groups. The matrix is input into the core function of the selected clustering algorithm, and the algorithm will automatically divide the machine groups into several clusters according to the similarity. For example, in hierarchical clustering, the two machine groups with the highest similarity are first connected, and then gradually merged according to certain linking criteria to form a clustering tree. By setting a similarity threshold to cut the tree, the initial machine group cluster division can be obtained.

[0033] S214. The initial machine group cluster division is optimized and verified to generate the final several machine group clusters.

[0034] 1. Calculate the clustering evaluation index of each machine group cluster in the initial machine group cluster division; 2. Determine whether the clustering evaluation index meets the preset qualified threshold; 3. If it meets, the initial machine group cluster division is confirmed as the final several machine group clusters.

[0035] 4. If the clustering evaluation index does not meet the preset qualified threshold, adjust the hyperparameters of the clustering algorithm model; Based on the adjusted hyperparameters, re-execute the clustering analysis; Determine whether the clustering evaluation index of the machine group cluster division obtained after re-clustering meets the preset qualified threshold. If it meets, the machine group cluster division after re-clustering is confirmed as the final several machine group clusters. If it does not meet, iteratively execute the steps of adjusting the hyperparameters and re-clustering until the clustering evaluation index meets the preset qualified threshold or the maximum number of iterations is reached.

[0036] Specifically, after obtaining the initial clusters, the algorithm calculates one or more quantitative mathematical indicators to evaluate the quality of this clustering, and the indicator is the silhouette coefficient; for each unit in the cluster, calculate its average distance with other units in the same cluster (compactness a), and then calculate its average distance with all units in the nearest other cluster (separation b), and the silhouette coefficient of this unit is (b-a) / max(a, b). The average of the silhouette coefficients of all units is the silhouette coefficient of the entire partition, which ranges between [-1, 1]. The calculated indicator is compared with the pre-set qualified threshold value, which is pre-set based on a large amount of experimental experience and domain knowledge, for example, if the silhouette coefficient is greater than 0.5, it is considered that the structure of the grouping is reasonable. If the quality indicator of the initial partition is qualified, the system determines that the partition is good enough and does not need to be further optimized. The process ends and the initial partition is output as the final solution for subsequent equivalent modeling.

[0037] Since the initial result is not up to standard, the algorithm automatically adjusts the hyperparameters of the clustering model; based on the new hyperparameters after adjustment, the entire clustering process is re-executed; the clustering evaluation indicators of the new partition are calculated, and it is judged again whether it meets the standard; this process will be repeated until a result that meets the standard is produced, or the maximum number of iterations (a pre-set safety limit to prevent infinite loops) is reached; even if it does not meet the standard, the iteration will stop when the maximum number of iterations is reached, and the partition with the best indicator in the history iteration is selected as the final result, ensuring that the output is the current optimal solution.

[0038] S3. Based on the impedance characteristic data of each unit in the cluster, the equivalent impedance characteristic of the current cluster is calculated, and the equivalent frequency domain network equivalent FDNE unit corresponding to the current cluster is determined according to the equivalent impedance characteristic; Here, the equivalent impedance characteristic refers to the overall external impedance characteristic of a cluster in a wide frequency range. It is not a single value, but a discrete impedance-frequency characteristic curve composed of a series of frequency points and their corresponding equivalent complex impedance (including real and imaginary parts) data points, which represents the equivalent impedance characteristic of the cluster to the outside at all frequencies from the perspective of the power grid.

[0039] Here, the equivalent frequency domain network equivalent unit is a mathematical model or circuit module constructed in simulation software (PSCAD / EMTDC) for accurately simulating the equivalent impedance characteristic of the cluster in the frequency domain. Its definition is: a two-port or multi-port black box model whose frequency domain response (i.e. the characteristic of impedance varying with frequency) is exactly the same as the curve defined by the equivalent impedance characteristic. In simulation, it is used to replace all detailed new energy unit models in the cluster while preserving the wide frequency dynamic characteristics of the original cluster, thereby greatly simplifying the complexity of the simulation network. Specifically as follows: S311. Obtain the complex impedance data of all new energy generating units in the current unit cluster under the same frequency sequence; S312. Perform parallel equivalent calculations on all complex impedance data under the same frequency sequence to obtain the equivalent complex impedance of the current unit cluster at each frequency point; S313. The equivalent impedance characteristics of the current cluster are constituted by the equivalent complex impedances at all frequency points.

[0040] Specifically, from the raw data obtained from S1, sequences with the same frequency within the current machine cluster are filtered out. Complex impedance data below For a single frequency point The derivation is achieved through impedance → admittance → total admittance → equivalent impedance: Complex impedance Admittance Its reciprocal (complex number operations): The total admittance is the complex sum of the admittances of all units within the cluster. : The reciprocal of the total admittance is the equivalent complex impedance at that frequency. : For all frequency points Repeat step S312 to obtain a set of frequency-equivalent impedance data pairs: This set describes the broadband impedance characteristic curves of the cluster.

[0041] In this embodiment, the equivalent frequency domain network equivalent FDNE unit corresponding to the current cluster is determined based on the equivalent impedance characteristics, including the following: S321. Organize the frequency sequence in the equivalent impedance characteristics and the real and imaginary parts of the equivalent complex impedance corresponding to each frequency point according to a preset format; S322. Import the organized data into the FDNE model building interface of the simulation platform; S323. Based on the organized data, generate equivalent FDNE elements representing the current cluster in the simulation platform. The frequency response characteristics of the equivalent FDNE elements are consistent with the equivalent impedance characteristics.

[0042] The data obtained from S313 (frequency sequence, and the real and imaginary parts of the equivalent complex impedance at each frequency point) is organized according to the FDNE module data format required by the simulation software, typically a three-column data table: frequency, real part, and imaginary part. This data table is then imported or entered into the FDNE model creation interface of the simulation software. The software will automatically generate an equivalent frequency domain network model based on this data. The frequency response of this model in the simulation will perfectly match the provided equivalent impedance characteristic data, thus accurately representing the physical cluster in the simulation.

[0043] S4. Construct a function with the optimization objective of maximizing the stability margin and minimizing the total harmonic distortion rate, and with the key parameters of each equivalent frequency-domain network equivalent FDNE unit as the optimization variables, and solve the optimal solution set of the function; Function The expression of the function is as follows: Wherein: is the optimization variable vector, the components of which are composed of the key parameters of each equivalent FDNE unit, is the system stability margin, is the total harmonic distortion rate of the current, is the weight coefficient, when is close to 1, the optimization process is more focused on maximizing the stability margin, and when is close to 0, the optimization process is more focused on minimizing the harmonic distortion rate, is the phase margin at a specific frequency , , are the minimum and maximum specific frequencies respectively, is the highest harmonic number considered, is the effective value of the nth harmonic component of the grid-connected current, is the effective value of the fundamental component of the grid-connected current. Specifically, the optimization variable

[0044] is the key parameter in each FDNE unit that can be adjusted and can affect the impedance frequency characteristics thereof; if the FDNE is realized by an equivalent RLC circuit, the variable can be the values of R, L and C; if the FDNE is a transfer function model based on rational function fitting, the variable can be the coefficients of the numerator and denominator polynomials of the transfer function; if the FDNE contains an equivalent of the control loop, the variable can be the controller gain, filter cutoff frequency, etc. Define a reasonable variation range (optimization space) for each variable to ensure that the optimized parameters are physically achievable and reasonable.

[0045] Solve the optimal solution set: select a non-dominated sorting genetic algorithm, which generates a set of candidate parameters , which is used to update the corresponding parameters of all FDNE units in the full-field equivalent simulation model; extract the current stability margin and the harmonic distortion rate from the simulation results, and calculate the objective function value ​The optimization algorithm determines whether to converge or generate a next batch of better candidate parameters according to the objective function value; when the maximum number of iterations is reached or the objective function improvement is less than a certain tolerance, the iteration stops; the algorithm outputs a set of optimal solutions, which contains multiple optimal schemes, each of which represents a best trade-off between stability and harmonic performance.

[0046] S5. According to the actual electrical topology of the new energy station, the optimized equivalent frequency domain network equivalent FDNE units are connected to construct a full-field equivalent simulation model. Based on the optimized FDNE units, the actual electrical topology and parameters of the new energy station (including geographical / electrical layout such as unit cluster, collection line, convergence point, main transformer location, and component parameters such as cable / sea cable type, length, unit impedance, transformer rated parameter, short-circuit impedance, etc.), simulation model construction is carried out in electromagnetic transient simulation software such as PSCAD / EMTDC and MATLAB / Simulink: first, component placement, according to the position relationship of the topology graph, arrange the FDNE units of each unit cluster, the main transformer model of the station, and the equivalent power source model of the grid on the simulation canvas; electrical connection, through software line components and connectors, connect the output end of the FDNE unit in the same cluster to the corresponding collection line, and the multiple collection lines converge to the bus, and then connect the main transformer and the equivalent power source of the grid; finally, complete the parameter setting, input the actual resistance, inductance, and capacitance parameters for the line components, set the nameplate and impedance value for the transformer, and configure the short-circuit capacity and other parameters for the equivalent grid model, and assign the parameters obtained by S4 optimization to the corresponding FDNE unit to ensure that it represents the characteristics of the optimized cluster. After the above operations are completed, a full-field equivalent simulation model including the grid connection point is constructed, which is a complete and operable circuit network. This model lays the foundation for calculating the equivalent impedance characteristics of the grid connection point of the new energy station in step S6, and only needs to run the simulation and call the impedance scanning function to quickly and accurately obtain the port impedance of the station and complete the stability evaluation.

[0047] S6. Calculate the equivalent impedance characteristics of the grid connection point of the new energy station through the full-field equivalent simulation model.

[0048] Calculating the equivalent impedance characteristics of the grid connection point of the new energy station includes the following steps: S611. Connect the harmonic impedance scanning module at the grid connection point of the new energy station in the full-field equivalent simulation model; S612. Set the scanning parameters of the harmonic impedance scanning module, including the starting frequency, the ending frequency, and the frequency interval; S613. Run the full-field equivalent simulation model, inject a wideband voltage small perturbation to the grid connection point through the harmonic impedance scanning module, and measure the current response of the grid connection point; The broadband voltage small perturbation is a harmonic voltage sequence containing multiple frequency components, and the expression is: wherein: is the broadband voltage small perturbation, is the upper limit of the harmonic order is the voltage amplitude of the first frequency component, is the frequency value of the first frequency component, is the phase offset of the first frequency component, is the continuously changing independent variable time.

[0049] S614. According to the broadband voltage small perturbation and the current response, the equivalent impedance frequency characteristic of the grid-connected point of the new energy station is calculated.

[0050] Specifically, the grid-connected point of the station and the main grid is located, and a harmonic impedance scanning module is introduced from the simulation software component library. The module has the functions of generating a multi-frequency excitation signal, measuring voltage and current response with high precision, configuring the scanning parameters of the module, determining the starting frequency (starting from a very low frequency such as 0.1Hz or 1Hz slightly higher than direct current, covering the subsynchronous oscillation risk), the termination frequency (set to a high enough value such as 2kHz or 5kHz, covering the harmonic resonance frequency band) and the frequency interval (define the scanning resolution such as 1Hz, the smaller the interval, the higher the accuracy but the simulation time increases).

[0051] Secondly, run the full-field equivalent simulation model, and the harmonic impedance scanning module automatically injects a broadband voltage small perturbation signal into the grid-connected point , ensures that the system works in the linear interval, does not trigger protection or change the operating state, and at the same time synchronously measures and records the current response of the grid-connected point caused by the perturbation ; after the simulation is completed, the module internal algorithm first performs fast Fourier transform on the time domain signals and respectively to obtain the voltage components and the current components in the frequency domain, and then calculates the complex impedance according to the frequency domain form of Ohm's law at each frequency point ; finally, all frequency points and their corresponding complex impedance values are integrated to form a complete impedance-frequency characteristic curve, which serves as the basis for stability evaluation. After the Nyquist diagram or Bode diagram is drawn in combination with the grid impedance curve, through the impedance criterion, it can accurately predict whether the system has subsynchronous / ultrasynchronous oscillation or harmonic resonance risk and stability margin, so as to solve the technical problems of impedance calculation and stability analysis of large new energy stations.

[0052] The above method steps are described in detail below in conjunction with a specific experimental scenario: Referring to Figure 6 , the topology diagram of a certain offshore wind farm, #53, #47, #62, #63, and #64, a total of 5 11 MW wind turbines (all normal board card parameters) are connected to the grid. To improve power generation capacity, #48 wind turbine (spare board card parameters) is planned to be connected to the grid. After #48 unit is connected to the grid, voltage abnormal fluctuation occurs at the grid connection point of the station, and FFT analysis shows that there is a significant 70 Hz super-synchronous component, as shown in Figure 7 , the surface system occurs unstable oscillation.

[0053] 1. Based on the RTLAB hardware-in-the-loop test system, impedance scans are performed on wind turbines of normal board card parameters and spare board card parameters at different power points (0.1Pn-1.0Pn), and detailed wideband impedance characteristic data sets of each unit are obtained. All the obtained unit data are input into the preset clustering algorithm model, the impedance amplitude frequency curve, phase frequency curve and resonance point information of each unit are extracted, and the impedance amplitude similarity, phase angle similarity and resonance point distribution similarity between any two units are calculated; according to the preset weight coefficient (higher weight is given to the resonance point distribution), the three similarities are weighted and summed to obtain the comprehensive similarity. Based on the comprehensive similarity matrix, an initial cluster division is generated. As shown in Figure 8 , the results show that the 5 normal board card units are automatically divided into one cluster due to the high similarity of impedance characteristics; while the #48 spare board card unit is identified as another cluster due to the significant difference in impedance characteristics. The silhouette coefficient of this initial division is calculated, and the index is excellent (>0.6), confirming that the clustering result is effective, and finally two unit clusters are generated.

[0054] 2. The complex impedance data of all units in the cluster at the same frequency sequence are obtained, and the parallel equivalent calculation of the complex impedance data at each frequency point is performed to obtain the equivalent impedance characteristics of the 5 normal board card units; while the 1 spare board card unit itself is a cluster, and its impedance characteristics are the equivalent impedance characteristics of the cluster. The equivalent impedance characteristic data of the two clusters are imported into the FDNE model construction interface of PSCAD according to the format, and two equivalent frequency domain network equivalent FDNE units respectively representing the 5 normal board card units and the 1 spare board card unit are generated.

[0055] 3. An optimization function is constructed to improve the system stability margin and reduce the harmonic distortion rate; the key parameters of the two FDNE units are used as optimization variables, and the optimal FDNE unit parameter set is obtained by solving the optimization algorithm. According to the actual electrical topology of the wind farm, the two optimized FDNE units are connected, and a complete full-field equivalent simulation model is constructed in PSCAD.

[0056] 4. In the constructed full-field equivalent simulation model, a harmonic impedance scanning module is connected to the point of common coupling; the scanning parameters (start frequency 0.1 Hz, end frequency 2000 Hz, interval 1 Hz) are set; the simulation is run, the module automatically injects a wide-frequency voltage small disturbance into the point of common coupling and measures the current response; the equivalent impedance frequency characteristics of the point of common coupling of the wind farm are calculated according to the disturbance and the response.

[0057] 6-unit operation: in the model, the FDNE units of 5 normal board card units and 1 standby board card unit are put into operation at the same time, the scenario after #48 unit is connected to the grid is simulated, the Bode diagram of the open-loop transfer function of the system is calculated, as shown in Figure 9 , there is an impedance amplitude intersection point near 69Hz, and the phase difference at this point is 185.6° (<-180°), which determines that the system is unstable. The analysis result is consistent with the 70Hz oscillation phenomenon observed in the field.

[0058] 5-unit operation: in the model, only the FDNE units of 5 normal board card units are put into operation, the scenario of 5 normal units running is simulated, and the calculation result is shown in Figure 10 , the phase difference near 69Hz is 161° (> -180°), which determines that the system is stable.

[0059] The conclusion shows that in this case, #48 unit (1 standby board card unit) destroys the stability of the original 5 normal board card units due to the difference in impedance characteristics, the prediction result is completely consistent with the actual situation, and the engineering application accuracy and effectiveness of the new energy power station impedance calculation method of the present application are effectively verified.

[0060] It can be understood that those skilled in the art can combine various embodiments in each of the above embodiments according to the teachings of the above embodiments to obtain various embodiments of the technical solutions.

[0061] The above only describes the preferred embodiments of the present application and is not intended to limit the present application, and any modifications, equivalent replacements and improvements made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A new energy station impedance calculation method, characterized in that, The method comprises the following steps: acquiring wideband impedance characteristic data of each new energy unit in different operating conditions in a new energy station; inputting the wideband impedance characteristic data of each new energy unit into a preset clustering algorithm model for clustering analysis to generate a plurality of unit clusters; based on the impedance characteristic data of each unit in each unit cluster, calculating the equivalent impedance characteristic of the current cluster, and determining the equivalent frequency domain network equivalent FDNE unit corresponding to the current cluster according to the equivalent impedance characteristic; constructing a function with the optimization objectives of maximizing the stability margin and minimizing the harmonic distortion rate, taking the key parameters of each equivalent frequency domain network equivalent FDNE unit as optimization variables, and solving the optimal solution set of the function; connecting the optimized equivalent frequency domain network equivalent FDNE units according to the actual electrical topology of the new energy station to construct a full-field equivalent simulation model; calculating the equivalent impedance characteristic of the new energy station grid connection point through the full-field equivalent simulation model.

2. The method of claim 1, wherein, The method comprises the following steps: extracting impedance amplitude-frequency curve, impedance phase-frequency curve and resonance frequency point information of each unit from the wideband impedance characteristic data, and calculating impedance amplitude similarity, impedance phase angle similarity and resonance point distribution similarity between any two new energy units based on the extracted data information; determining the comprehensive similarity between the any two new energy units according to the impedance amplitude similarity, impedance phase angle similarity and resonance point distribution similarity; generating an initial unit cluster division based on the comprehensive similarity between all new energy units; optimizing and verifying the initial unit cluster division to generate the final plurality of unit clusters.

3. The method of claim 2, wherein, The method comprises the following steps: obtaining preset amplitude weight coefficient, phase angle weight coefficient and resonance point weight coefficient; weighting and summing the impedance amplitude similarity, impedance phase angle similarity and resonance point distribution similarity according to the amplitude weight coefficient, phase angle weight coefficient and resonance point weight coefficient, and determining the calculation result as the comprehensive similarity.

4. The method of claim 2, wherein, The method comprises the following steps: calculating the clustering evaluation index of each unit cluster in the initial unit cluster division; determining whether the clustering evaluation index reaches a preset qualified threshold; if so, confirming that the initial unit cluster division is the final plurality of unit clusters.

5. The method of claim 4, wherein, The method comprises the following steps: if the clustering evaluation index does not reach the preset qualified threshold, adjusting the hyperparameters of the clustering algorithm model; re-executing the clustering analysis based on the adjusted hyperparameters; determine whether the clustering evaluation index of the unit cluster obtained after re-clustering reaches the preset qualified threshold; if yes, confirm that the unit cluster obtained after re-clustering is the final unit cluster; if not, iteratively perform the steps of adjusting the hyperparameters and re-clustering until the clustering evaluation index reaches the preset qualified threshold or the maximum number of iterations is reached.

6. The method of claim 1, wherein, The equivalent impedance characteristic of the current cluster is calculated based on the impedance characteristic data of each unit in each unit cluster, including: Obtain the complex impedance data of all new energy units in the current unit cluster under the same frequency sequence; Parallel equivalent calculation is performed on all complex impedance data under the same frequency sequence to obtain the equivalent complex impedance of the current unit cluster at each frequency point. The equivalent impedance characteristic of the current cluster is composed of the equivalent complex impedance of all frequency points.

7. The method of claim 6, wherein, The equivalent frequency domain network equivalent FDNE unit corresponding to the current cluster is determined according to the equivalent impedance characteristic, including: Organize the frequency sequence and the real and imaginary parts of the equivalent complex impedance corresponding to each frequency point in the equivalent impedance characteristic according to a preset format; Import the organized data into the FDNE model construction interface of the simulation platform; Based on the organized data, an equivalent frequency domain network equivalent FDNE unit representing the current cluster is generated in the simulation platform, and the frequency response characteristic of the equivalent frequency domain network equivalent FDNE unit is consistent with the equivalent impedance characteristic.

8. The method of claim 1, wherein, The function with the optimization objective of maximizing the stable margin and minimizing the harmonic distortion rate is constructed, including: Function The expression of the function f is as follows: in: To optimize the variable vector, its components are composed of the key parameters of each equivalent FDNE element. For system stability margin, The total harmonic distortion of the current. For weighting coefficients, when When the value is close to 1, the optimization process focuses more on maximizing the stability margin. As the value approaches zero, the optimization process focuses more on minimizing the harmonic distortion rate. To at a specific frequency Phase margin below, , These are the minimum specific frequency and the maximum specific frequency, respectively. For the highest harmonic order considered, The first of the grid-connected current RMS value of subharmonic components This represents the effective value of the fundamental component of the grid-connected current.

9. The method of claim 1, wherein, The equivalent impedance characteristic of the new energy station grid-connected point is calculated by the full-field equivalent simulation model, including: Access a harmonic impedance scanning module at the new energy station grid-connected point of the full-field equivalent simulation model; Set the scanning parameters of the harmonic impedance scanning module, including the starting frequency, the ending frequency and the frequency interval; Run the full-field equivalent simulation model, inject a wideband voltage small perturbation into the grid-connected point through the harmonic impedance scanning module, and measure the current response of the grid-connected point; According to the wideband voltage small perturbation and the current response, the equivalent impedance frequency characteristic of the new energy station grid-connected point is calculated.

10. The method of claim 9, wherein, The wideband voltage small perturbation is a harmonic voltage sequence containing multiple frequency components, and the expression is: wherein: V is a wideband voltage small perturbation, N is a harmonic number upper limit V is a voltage amplitude of the V is a voltage amplitude of the V is a voltage amplitude of the V is a frequency value of the V is a phase offset of the V is a phase offset of the t is a continuously varying independent variable time.

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