Stability margin calculation method of new energy station grid-connected system, terminal and storage medium

Abstract

The invention provides a stability margin calculation method of a new energy station grid-connected system, a terminal and a storage medium. The method comprises the following steps: acquiring inverter output impedance and power grid side equivalent impedance of an initial new energy station grid-connected system under multiple working conditions; taking the ratio of the output impedance of the inverter to the equivalent impedance of the power grid side under the same working condition as an open-loop transfer function, and determining a gain margin and a phase margin of the new energy station grid-connected system under each working condition based on the open-loop transfer function under each working condition; determining the weakest working condition of the new energy station grid-connected system based on the gain margin and the phase margin of the new energy station grid-connected system under each working condition; and under the weakest working condition, based on the gain margin and the phase margin of the new energy station grid-connected system under different numbers of inverters connected in parallel, the maximum capacity expansion number is determined. According to the method, accurate quantification of the capacity expansion limit is realized, the system stability is ensured, and the capacity expansion potential of the station is fully excavated.

Description

Technical Field

[0001] This invention relates to the field of grid-connected system technology, and in particular to a method for calculating the stability margin of a new energy power plant grid-connected system, a terminal, and a storage medium. Background Technology

[0002] As the global energy structure shifts towards cleaner and lower-carbon energy, the grid-connected scale of new energy power plants, such as photovoltaic power plants, continues to grow rapidly. As an important component of the new power system, they play a crucial role in optimizing the energy structure and ensuring energy security. However, the large-scale integration of new energy power plants, especially the clustered parallel operation of a large number of photovoltaic grid-connected inverters, has caused the power grid to exhibit significant weak grid characteristics, posing a severe challenge to system stability.

[0003] As the core power electronic equipment connecting new energy sources to the grid, photovoltaic inverters are used to expand their capacity as a major way to increase the capacity of power plants. However, the parallel connection of a large number of inverters can lead to a decrease in system stability margin and even trigger oscillations and instability.

[0004] In the existing technology, the evaluation method for the expansion of inverters in new energy power plants has obvious limitations: First, traditional expansion calculations mostly rely on empirical estimation or stability analysis under a single operating condition. For example, if the capacity that can be connected is roughly judged based on the grid short-circuit ratio, it is difficult to cover the entire life cycle operation scenario. This leads to either the expansion scale being limited by conservative design or insufficient stability margin after expansion due to improper parameter settings. Summary of the Invention

[0005] This invention provides a method, terminal, and storage medium for calculating the stability margin of a new energy power station grid-connected system, in order to solve the problem of low stability margin in the grid-connected system of new energy power stations caused by inaccurate inverter capacity expansion in the prior art.

[0006] In a first aspect, embodiments of the present invention provide a method for calculating the stability margin of a new energy power station grid-connected system, including:

[0007] The inverter output impedance and grid-side equivalent impedance of the initial renewable energy power plant grid-connected system under multiple operating conditions are obtained; the initial renewable energy power plant grid-connected system includes one inverter.

[0008] The ratio of the inverter output impedance to the grid-side equivalent impedance under the same operating condition is used as the open-loop transfer function. Based on the open-loop transfer function under each operating condition, the gain margin and phase margin of the new energy power station grid-connected system under each operating condition are determined.

[0009] Based on the gain margin and phase margin of the new energy power station grid connection system under various operating conditions, the weakest operating condition of the new energy power station grid connection system is determined.

[0010] Under the weakest operating condition, based on the gain margin and phase margin of the grid-connected system of the new energy power station with different numbers of inverters connected in parallel, the maximum number of inverters that can be expanded to support the grid-connected system of the new energy power station is determined.

[0011] In a second aspect, embodiments of the present invention provide a terminal, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method as described in any possible implementation of the first aspect above.

[0012] Thirdly, embodiments of the present invention provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method as described in any possible implementation of the first aspect above.

[0013] This invention provides a method, terminal, and storage medium for calculating the stability margin of a renewable energy power plant grid-connected system. The method first obtains the inverter output impedance and grid-side equivalent impedance of the initial renewable energy power plant grid-connected system under multiple operating conditions. The initial renewable energy power plant grid-connected system includes one inverter. The ratio of the inverter output impedance to the grid-side equivalent impedance under the same operating condition is used as the open-loop transfer function. Based on the open-loop transfer function under each operating condition, the gain margin and phase margin of the renewable energy power plant grid-connected system under each operating condition are determined. Then, based on the gain margin and phase margin of the renewable energy power plant grid-connected system under each operating condition, the weakest operating condition of the renewable energy power plant grid-connected system is determined. Under the weakest operating condition, based on the gain margin and phase margin of the renewable energy power plant grid-connected system with different numbers of inverters connected in parallel, the maximum number of inverters that can be expanded in the renewable energy power plant grid-connected system is determined. The above method breaks through the limitations of traditional single-condition analysis. By traversing different conditions, it comprehensively captures the stability risks of the system throughout its entire life cycle. By focusing on the weakest condition, it ensures that the capacity expansion assessment is based on the most stringent scenario, avoiding grid connection risks caused by misjudgment of local conditions. Based on the margin quantification index, it determines the maximum number of units that can be expanded. Compared with traditional empirical estimation methods, it achieves accurate quantification of the expansion limit, which not only ensures system stability but also fully explores the expansion potential of the power station, providing a scientific basis for the safe planning and phased expansion of new energy power stations. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a flowchart illustrating the implementation of the stability margin calculation method for a new energy power station grid-connected system provided in this embodiment of the invention.

[0016] Figure 2 This is a schematic diagram illustrating the determination of phase margin and gain margin based on the Nyquist curve provided in an embodiment of the present invention;

[0017] Figure 3 This is a schematic diagram of the time-domain response of the grid connection point when the system frequency domain has sufficient margin, as provided in the embodiments of the present invention.

[0018] Figure 4 This is a schematic diagram of the time-domain response of the grid connection point when the frequency domain margin of the system provided in this embodiment of the invention is insufficient;

[0019] Figure 5 This is a schematic diagram of the Nyquist curve following the change in the number of inverters connected in parallel, provided by an embodiment of the present invention;

[0020] Figure 6 This is a schematic diagram of the simulation model structure of the new energy power station grid connection system provided in the embodiment of the present invention;

[0021] Figure 7 This is a schematic diagram of the amplitude-frequency curve and phase-frequency curve after applying a disturbance to the grid connection point in the simulation model of the grid connection system of the new energy power station provided in the embodiment of the present invention. Detailed Implementation

[0022] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of the invention. However, those skilled in the art will understand that the invention can be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods are omitted so as not to obscure the description of the invention with unnecessary detail.

[0023] To make the objectives, technical solutions, and advantages of the present invention clearer, specific embodiments will be described below in conjunction with the accompanying drawings.

[0024] See Figure 1 The document illustrates a flowchart of the stability margin calculation method for a new energy power station grid-connected system provided in this embodiment of the invention, detailed below:

[0025] S101: Obtain the inverter output impedance and grid-side equivalent impedance of the initial renewable energy power station grid-connected system under multiple operating conditions; the initial renewable energy power station grid-connected system includes one inverter.

[0026] In one possible implementation, the specific implementation process of S101 includes:

[0027] The inverter output impedance and grid-side equivalent impedance of the new energy power station grid-connected system under various operating conditions are obtained by the frequency sweep perturbation method.

[0028] In this embodiment, the initial structure and test benchmark of the new energy power station grid-connected system are first defined, and the initial grid-connected system topology is determined. This system includes an inverter, an output filter, collector lines, and equivalent circuits on the grid side. System benchmark parameters, including the inverter's rated power, filter parameters, initial equivalent impedance on the grid side, and control parameters, are recorded as the benchmark for subsequent impedance calculations.

[0029] Then, determine the parameter range for multiple operating conditions. Based on the actual operating scenarios of the system, set the "multiple operating conditions" that need to be covered, specifically including:

[0030] 1. Photovoltaic output levels: low power (20% of rated value), partial power (50% of rated value), full power (100% of rated value), achieved by adjusting the inverter power command;

[0031] 2. Power grid strength level: strong power grid (short-circuit ratio SCR≥3), weak power grid (1≤SCR<3), and extremely weak power grid (SCR<1). This is achieved by adjusting the equivalent inductance Lg and resistance Rg on the power grid side. For example, a weak power grid corresponds to a larger Lg.

[0032] When combining the above two parameters to form different operating conditions, ensure that the operating condition combinations cover typical scenarios such as "low power + strong grid" and "full power + weak grid", and include at least 5 combinations.

[0033] Secondly, it is necessary to build a frequency sweeping disturbance test platform. At the grid connection point of the initial new energy power plant grid connection system, a frequency sweeping test device should be set up to measure the output impedance of the new energy and the equivalent impedance of the grid side at the grid connection point under different operating conditions using the frequency sweeping disturbance method.

[0034] Specifically, frequency sweeping disturbances and data acquisition are performed on a case-by-case basis. For each case, the following operations are performed in sequence:

[0035] (1) Adjust the system to the target operating condition: Set the photovoltaic output to the target power, adjust the grid-side equivalent impedance to the target strength, and wait for the system to operate stably;

[0036] (2) Inject frequency sweep disturbance: Inject disturbance at each frequency point, with each frequency point lasting for ≥10 power grid cycles to ensure signal stability;

[0037] (3) Synchronous data acquisition: Record the voltage and current changes at each frequency point and store them as time-domain waveform files.

[0038] After data acquisition, the impedance values ​​under each operating condition are calculated. First, frequency domain analysis is performed on the acquired data for each operating condition: Fourier transforms are performed on the voltage and current change signals to obtain the voltage disturbance amplitude and current response amplitude at each frequency. Then, the impedance is calculated: according to the impedance definition Z = ΔU / ΔI, the inverter output impedance under each operating condition is calculated; the grid-side equivalent impedance |Z grid (jω)|=|ΔU grid (jω)| / |ΔI grid (jω)|. Where ΔU grid (jω) represents the grid-side voltage disturbance, ΔI grid (jω) represents the current disturbance flowing into the power grid.

[0039] Record phase characteristics: Synchronously calculate inverter output impedance Z at each frequency inv (jω) and the grid-side equivalent impedance Z grid Phase angle ∠Z of (jω) inv (jω), ∠Z grid (jω).

[0040] Finally, the impedance datasets under multiple operating conditions are organized. The calculation results are stored according to the operating condition, forming a four-dimensional dataset of "operating condition-frequency-impedance amplitude-phase". This four-dimensional dataset includes: Z-axis impedance for each operating condition. inv The amplitude and phase frequency curves of (s); the Z-frequency response curve for each operating condition. grid (s) Amplitude-frequency and phase-frequency curves; impedance eigenvalues ​​at key frequency points (such as the resonant risk band), including amplitude and phase. This four-dimensional dataset serves as the basic input for subsequent calculations of the open-loop transfer function and stability margin.

[0041] S102: The ratio of the inverter output impedance to the grid-side equivalent impedance under the same operating condition is used as the open-loop transfer function, and based on the open-loop transfer function under each operating condition, the gain margin and phase margin of the new energy power station grid-connected system under each operating condition are determined.

[0042] In this embodiment, the Nyquist criterion is used to construct the open-loop transfer function, which is L(s) = Z. grid (s) / Z inv (s);

[0043] Where L(s) represents the open-loop transfer function, s represents the complex variable, and Z... grid (s) represents the equivalent impedance transfer function on the grid side, Z inv (s) represents the inverter output impedance transfer function.

[0044] In one possible implementation, the specific implementation process of S102 includes:

[0045] Plot the Nyquist curves of the open-loop transfer function under various operating conditions;

[0046] For any Nyquist curve corresponding to any operating condition, the difference between the phase of the intersection point of the Nyquist curve and the unit circle and the first preset phase is taken as the phase margin of the operating condition; and the point in the Nyquist curve with the first preset phase is taken as the first target point, and the distance between the first target point and the critical reference point is taken as the gain margin.

[0047] In this embodiment, firstly, the Nyquist curve of L(s) is plotted, as follows: Figure 2 As shown, we determine the case where the Nyquist curve bypasses the point (-1, j0) to determine the closed-loop stability and margin.

[0048] Specifically, in the Nyquist curve, the unit circle is the set of all points 1 unit away from the origin (0, j0), representing the open-loop transfer function amplitude L(jω) = 1. Find the intersection point of the Nyquist curve with the unit circle; the frequency corresponding to this intersection point is the gain crossover frequency ω0. At this point, the system's open-loop gain is exactly 1, representing the critical point where the gain changes from greater than 1 to less than 1. Record the phase angle ∠L(jω0) of the point on the Nyquist curve corresponding to the gain crossover frequency ω0, which is the angle between this point and the positive real axis, ranging from -180° to 180°. The phase margin is then the difference between this phase angle ∠L(jω0) and -180°, expressed by the formula: PM = 180° + ∠L(jω0).

[0049] For example, if the phase at the intersection point is -130°, then the phase margin PM = 180° + (-130°) = 50°, which means that the system still has a phase redundancy of 50° in the gain critical state.

[0050] Gain margin reflects the gain redundancy of the system at the "phase critical state". It is calculated based on the point with a phase of -180° in the Nyquist curve, as follows:

[0051] First, the initial preset phase can be -180°. Find a point on the Nyquist curve where the phase angle is -180°, meaning the angle between this point and the positive real axis is exactly -180°. The frequency corresponding to this point is the phase crossover frequency ω. pc At this point, the system phase reaches the critical unstable phase. Then, the amplitude |L(jω) at the point on the Nyquist curve corresponding to the phase crossing frequency is recorded. pc | represents the distance from that point to the origin. The gain margin is the reciprocal of the amplitude in decibels, calculated using the formula:

[0052]

[0053] For example: if the amplitude at this point is 0.5, then the gain margin = 20log10 (1 / 0.5) = 6dB, which means that the system can increase the gain by another 6dB before it becomes unstable when it is in the critical phase state.

[0054] In one possible implementation, the gain margin and phase margin can also be determined using the amplitude-frequency response curve and phase-frequency response curve of the open-loop transfer function, as detailed below:

[0055] Phase margin reflects the phase redundancy of the system when the open-loop gain is 1 (0dB). The steps are as follows:

[0056] Step 1: On the amplitude-frequency response curve (vertical axis is amplitude; horizontal axis is frequency), find the frequency point where the amplitude is 0dB, that is, the open-loop transfer function amplitude |L(jω0)| = 1. This frequency is called the gain crossover frequency ω0. This point is the critical frequency at which the system's open-loop gain transitions from greater than 1 to less than 1.

[0057] Step 2: On the phase frequency response curve (vertical axis is phase; horizontal axis is frequency), find the phase angle |L(jω0)| corresponding to ω0 determined in Step 1, which is the phase of the open-loop transfer function at that frequency.

[0058] Step 3: The phase margin is the difference between the phase angle |L(jω0)| and -180°, and the formula is: PM=180°+∠L(jω0).

[0059] Gain margin reflects the gain redundancy of the system when the open-loop phase is -180°. The steps are as follows:

[0060] Step 1: On the phase-frequency response curve (vertical axis is phase; horizontal axis is frequency), find the frequency point where the phase is -180°. This frequency is called the phase crossover frequency ω. pc This point is the critical frequency at which the open-loop phase of the system reaches the critical instability phase.

[0061] Step 2: On the amplitude-frequency response curve (vertical axis is amplitude; horizontal axis is frequency), find the ω determined in Step 1. pc The corresponding amplitude |L(jω) pc )|, which is the amplitude of the open-loop transfer function at that frequency, expressed in dB.

[0062] Step 3: The gain margin is the negative of the amplitude, since the amplitude is expressed in dB. Therefore, the formula is: GM(db)=-|L(jω) pc )|.

[0063] S103: Based on the gain margin and phase margin of the new energy power station grid connection system under various operating conditions, determine the weakest operating condition of the new energy power station grid connection system.

[0064] In this embodiment, it can first be determined whether the gain margin under each operating condition is greater than the preset gain margin and the phase margin is greater than the preset phase margin. If the gain margin under each operating condition is greater than the preset gain margin and the phase margin is greater than the preset phase margin, then the operating condition is relatively stable.

[0065] Secondly, assuming that the initial grid-connected system of the new energy power station is relatively stable under different operating conditions, the gain margin and phase margin of each operating condition are compared respectively, and the weakest operating condition can be selected based on the gain margin or phase margin.

[0066] Specifically, when selecting the weakest operating condition based on gain margin, if the gain margin of the current operating condition is the minimum of the corresponding gain margins of all operating conditions, and the phase margin is in the middle to lower range of all operating conditions, then this operating condition is considered the weakest operating condition. Similarly, when selecting the weakest operating condition based on phase margin, if the phase margin of the current operating condition is the minimum of the corresponding phase margins of all operating conditions, and the gain margin is in the middle to lower range of all operating conditions, then this operating condition is considered the weakest operating condition.

[0067] In one possible implementation, the specific implementation process of S103 includes:

[0068] The stability margin is obtained by weighted summation of the gain margin and the phase margin.

[0069] The operating condition with the smallest stability margin is taken as the weakest operating condition of the new energy power station grid connection system.

[0070] In this embodiment, a weighted summation method is first used to integrate the gain margin and phase margin into a single stability margin index to quantify the overall stability of each operating condition; then the weakest operating condition is selected.

[0071] Specifically, this embodiment first determines the weights of GM and PM based on engineering requirements. PM has a higher weight in weak grid scenarios, while GM has a higher weight in strong grid scenarios. For example, the weight of GM is set to w1 = 0.4, and the weight of PM is set to w2 = 0.6, with a sum of 1. Then, GM and PM are normalized to the [0,1] interval to eliminate dimensional differences. Finally, based on the formula M = w1 * GM... norm +w2*PM norm Determine the stability margin. Among them, GM norm For the normalized gain margin, PM norm This represents the normalized phase margin. Compare the stability margins M for all operating conditions and identify the condition with the smallest M value as the weakest operating condition.

[0072] Furthermore, in order to improve the accuracy of the weakest working condition, after the weakest working condition is determined by the above method, this embodiment can verify whether the GM and PM of the weakest working condition are both lower values ​​among all working conditions. For example, whether the GM of the weakest working condition is located in the last N positions of the GM sequence (sorted from largest to smallest) of all working conditions, and whether the PM is located in the last N positions of the PM sequence (sorted from largest to smallest) of all working conditions. If so, the working condition is confirmed as the weakest working condition.

[0073] As can be seen from the above embodiments, this embodiment obtains the stability margin by weighted summation of gain margin and phase margin, and takes the operating condition with the smallest stability margin as the weakest operating condition. This technical feature solves the problem of risk misjudgment that may be caused by a single margin index. Gain margin focuses on reflecting the system's ability to resist gain fluctuations, while phase margin focuses on reflecting its ability to resist phase shifts. The weighted fusion of the two can comprehensively evaluate the overall stability of the system. It can not only avoid potential risks that may be missed by relying on only a single margin index, making the identification of the weakest operating condition more comprehensive; it can also adapt to the stability requirements of different application scenarios through flexible adjustment of weight coefficients; the quantitative value of stability margin provides a clear benchmark for multi-condition comparison, making it easy to quickly locate the operating point with the highest risk, providing accurate target operating conditions for subsequent capacity expansion assessment and control parameter optimization, and improving the efficiency and reliability of system stability analysis.

[0074] S104: Under the weakest operating condition, based on the gain margin and phase margin of the grid-connected system of the new energy power station with different numbers of inverters connected in parallel, determine the maximum number of units that can be expanded in the grid-connected system of the new energy power station.

[0075] In one possible implementation, a time-domain simulation model of the new energy power station grid-connected system can also be established in a real-time digital simulation system for each of the typical operating conditions identified above.

[0076] Specifically, a small step change (such as a power command change, grid voltage phase disturbance, or load disturbance) is introduced under steady-state conditions to observe whether the transient response of the renewable energy power plant grid-connected system exhibits continuous oscillations. The time-domain response results are compared with the frequency-domain margin prediction. If the frequency-domain analysis shows sufficient phase margin, the time-domain step response should exhibit underdamped but convergent oscillations without divergence, such as... Figure 3 As shown. If the frequency domain analysis predicts near instability (with very small or even negative margin), then the time domain simulation may show low-frequency or resonant oscillations, such as... Figure 4 As shown, this frequency-time domain combined approach cross-validates stability judgments, improving the reliability of conclusions. Simulation can verify some nonlinear or saturation factors not considered in frequency domain analysis, thus making the analysis more robust in engineering applications.

[0077] Finally, based on the frequency domain calculations and time domain simulation results, the stability margin level of the new energy power station is comprehensively evaluated. If insufficient stability margin is found under certain operating conditions, the reasons are analyzed. For example, at a specific frequency, the inverter output impedance and the equivalent impedance on the grid side may have similar amplitudes and a phase difference of nearly 180°, leading to resonance tendency. Improvement measures are then proposed, such as optimizing control parameters or increasing damping. Conversely, if sufficient margin is available under all operating conditions, the system is confirmed to be operating stably under the selected control strategy.

[0078] In one possible implementation, the specific implementation process of S104 includes:

[0079] S201: Gradually increase the number of inverters connected in parallel in the new energy power station grid-connected system, and calculate the gain margin and phase margin of the new energy grid-connected system under different numbers of inverters connected in parallel;

[0080] S202: The maximum number of inverters connected in parallel with a gain margin and a phase margin not less than the corresponding margin threshold shall be used as the maximum number of inverters to be expanded in the grid-connected system of the new energy power station.

[0081] In one possible implementation, the specific implementation process of S201 includes:

[0082] Based on formula Z inveq (s)=Z inv (s) / n calculates the inverter output impedance of the new energy grid-connected system under different numbers of inverters connected in parallel; and uses the initial grid-side equivalent impedance of the new energy power plant grid-connected system as the grid-side equivalent impedance of the new energy grid-connected system under different numbers of inverters connected in parallel; where, Z inveq (s) represents the inverter output impedance of the new energy grid-connected system when the number of inverters connected in parallel is n, Z inv (s) represents the initial inverter output impedance of the new energy power station grid-connected system; n represents the number of inverters connected in parallel;

[0083] The ratio of the inverter output impedance to the grid-side equivalent impedance under the weakest operating condition is used as the open-loop transfer function.

[0084] Based on the open-loop transfer function of the weakest operating condition, the gain margin of the new energy power station grid-connected system under the weakest operating condition is determined.

[0085] In one possible implementation, after S104, the method provided in this embodiment further includes:

[0086] A simulation model of a new energy power plant grid-connected system with an adjustable number of inverters in parallel is constructed. The simulation model includes a new energy power plant simulation model with an adjustable number of inverters in parallel, a grid-side simulation model, and a grid connection point simulation model.

[0087] Set the parameters corresponding to the weakest working condition to the simulation model, and apply a disturbance signal to the simulation model;

[0088] Run the simulation model and gradually increase the number of inverters connected in parallel. For each number of inverters connected in parallel, collect the grid connection point electrical signal of the simulation model under that number of inverters connected in parallel. Extract the dynamic performance parameters of the simulation model based on the grid connection point electrical signal, and determine whether the simulation model remains stable under that number of inverters connected in parallel based on the dynamic performance parameters.

[0089] If the simulation model remains stable at the maximum number of units expanded, and the simulation model becomes unstable at the first preset number of units expanded, then the maximum number of units expanded is determined as the critical value for the number of inverters expanded in the grid-connected system of the new energy power station; the first preset number of units is the value obtained by adding one to the maximum number of units expanded.

[0090] In this embodiment, while maintaining system stability, the number of inverters that can be safely expanded and the upper limit of total power are determined. The specific steps are as follows:

[0091] Step 1: First, define the initial conditions: Taking the initial grid-connected system of a new energy power station containing one inverter as the benchmark, record the inverter output impedance Z under the weakest operating condition. inv，1 (s), Equivalent impedance of the grid side Z grid (s) and stability margin M1 (including gain margin GM1 and phase margin PM1). Then set the stability margin threshold: according to engineering specifications, preset the minimum allowable stability margin M. For example, the margin threshold corresponding to the gain margin can be 6dB, the margin threshold corresponding to the phase margin can be 45°, and the margin threshold of the overall stability margin M can be set to 0.6, where M is a weighted value normalized to [0,1]. Finally, define the expansion step size: set the number of inverters added each time. To ensure accuracy, the expansion step size can be 1, and at the same time set the maximum number of units that can be tried.

[0092] Step 2: First, calculate the equivalent output impedance: For n inverters of the same model connected in parallel, ignoring the influence of small parameter differences between inverters, their equivalent output impedance Z can be approximated. inveq (s) represents the impedance Z of a single inverter. inv The result of (s) being in parallel with n, i.e., Z inveq (s)≈Z inv (s) / n, and assuming the grid strength is not improved, if the expanded grid is connected to the same common grid connection point, then the grid equivalent impedance Z grid (s) remains unchanged. In this way, the process of gradually increasing the station capacity from its current size can be simulated.

[0093] Secondly, construct the open-loop transfer function: The open-loop transfer function when n units are connected in parallel is: L(s) = Z grid / Z inveq = n·Z grid / Z inv ; where, Z inveq represents the equivalent output impedance of the inverter, n is the current number of parallel units, and n is a positive integer.

[0094] As n increases, the magnitude of the equivalent impedance of the inverter decreases geometrically, and the open-loop gain of the system L(s) increases linearly. This will cause the Nyquist curve to gradually approach the point (-1, j0), as Figure 5 shown Figure 5 shows the comparison diagram of the Nyquist curves for different values of the system equivalent impedance Zg (left) and the proportional gain K (right).

[0095] Step 3: Gradually increase the number of parallel units and evaluate the stability margin.

[0096] Specifically, the initial number of units n = 1. Taking M1 in Step 1 as the benchmark, if M1 ≥ Mmin, then continue to expand the capacity; n takes 2, 3,... in sequence. For each n, calculate the open-loop transfer function according to the method of calculating the open-loop transfer function mentioned above, and then calculate the Nyquist curve of L_n(s); determine the gain margin GMn and phase margin PMn of the system when the number of parallel inverter units is n through the Nyquist curve. Then calculate the corresponding stability margin Mn through the weighted summation method. If Mn ≥ Mmin, then the current value of n is the safe number of units, and continue to increase the number of parallel inverter units; if Mn+1 < Mmin, then stop expanding the capacity, and record the previous number of units n as the candidate maximum number of units. Among them, Mmin can be zero, that is, the Nyquist curve just passes through the point (-1, j0), and the system is in critical stability. At this time, the total number of inverters and the corresponding total output power are the expansion limit. For safety reasons, a certain margin can be left on this basis to determine the actual allowable maximum grid connection capacity. [[ID=2 and 5]]

[0097] Step 4: Verify the critical stability of the maximum expansion number of units.

[0098] [[ID=2 and 5]] For the candidate maximum number of units n max = n, apply a disturbance under the weakest working condition, such as a 10% voltage step, and verify through simulation or experiment to determine whether the system dynamic response does not show continuous oscillation; or whether the steady-state indicators (grid connection point voltage deviation and frequency deviation) are less than the corresponding thresholds, for example, the grid connection point deviation ≤ 2% * rated value, and the frequency deviation ≤ ±0.2 Hz; if so, confirm that n max is the maximum expansion number of units; if it fails, subtract 1 from n max and verify again until the stability requirements are met.

[0099] Step 5: Record the maximum number of units to be expanded and the corresponding stability margin; generate the "number of units - stability margin" relationship curve, mark the critical position of nmax, and provide an intuitive basis for engineering design; if Mmin is no longer satisfied when the initial number of units n=1, the inverter control parameters need to be optimized and recalculated.

[0100] In a practical application scenario, taking a photovoltaic power station in a certain district as an example, the project has a total installed capacity of 60MW, is boosted to 220kV for grid connection, and uses approximately 180 photovoltaic grid-connected inverters connected to the system. In this embodiment, a typical operating condition of 50% of the rated photovoltaic output power is selected for stability evaluation. It is assumed that the thermal power unit output is approximately 50% at this time, and the SVG (Static Var Generator) device in the station is inductively at full capacity, representing the operating point of partial output of the photovoltaic power station under a relatively weak grid scenario. For the above-mentioned new energy power station grid-connected system, the following expansion estimation and control parameter optimization process is performed:

[0101] Step 1: Impedance sweep frequency and margin calculation.

[0102] Under the above operating conditions, frequency scanning analysis was performed on the grid-connected system of the new energy power plant. Following the methods outlined in relevant technical specifications, a small disturbance was injected at the grid connection point, and the frequency domain impedance characteristics were obtained. The 38–40Hz frequency band was specifically selected for frequency sweep testing to obtain the inverter output impedance Z. inv Equivalent impedance Z on the grid side grid The amplitude and phase data for this frequency band are shown in Table 1. Table 1 shows the impedance sweep results of the new energy power station grid-connected system in the 38–40 Hz frequency band under the 0.5 pu condition.

[0103] Table 1

[0104]

[0105] As shown in Table 1, the output impedance amplitude of the photovoltaic inverter is approximately 35–38Ω around 38–40Hz, which is much larger than the equivalent grid impedance of 3.7–3.9Ω. The inverter impedance phase angle is close to +100°, while the grid impedance phase angle is approximately +78°. The inverter impedance phase angle is close to +90° and slightly exceeds 90°, indicating that it exhibits negative impedance characteristics in this frequency band. The grid impedance phase angle is slightly lower than +90°, indicating that the grid impedance is predominantly inductive with some damping. Based on the measured impedance data, the loop transfer function L(jω) = Z can be calculated. grid (jω) / Z inv The value of (jω) in this frequency range.

[0106] The Bode plot or Nyquist plot of the loop gain L(jω) obtained from this analysis shows that the open-loop gain is far below 0dB in the 38–40Hz frequency band, with no frequency point reaching the critical state of gain 1, and the system phase margin does not reach a dangerous value close to 0°. Therefore, under this operating condition, the photovoltaic grid-connected system has ample stability margin in the subsynchronous frequency band—a gain margin greater than 10 (>20dB) and a phase margin of approximately 160°. In other words, the Nyquist curve will not revolve around the point (-1,0), satisfying the generalized Nyquist stability criterion, and the system is transiently stable and controllable.

[0107] However, visual observation of the amplitude-frequency curve of L(s) alone is insufficient to rigorously determine the stability margin. It is also necessary to plot the Nyquist trajectory of the loop transfer function in conjunction with the grid impedance for quantitative judgment. This embodiment obtains clear gain margin and phase margin indices through the above calculations, providing a basis for system stability assessment.

[0108] Step 2: Impedance Model and Transfer Function. To deeply analyze the impedance characteristics of the inverter and the power grid, a small-signal model can be used to establish their respective frequency domain transfer functions. In the dq rotating coordinate system, the control loop of the inverter is linearized and modeled to obtain an analytical expression for the inverter's output impedance.

[0109] In one possible implementation, the inverter output impedance transfer function includes:

[0110]

[0111] Among them, R f T represents the magnitude of the equivalent negative impedance. f Z represents the time constant under the influence of external active power control. inv,L (s) represents the low-frequency negative impedance; ω PLL Let ξ represent the natural frequency of the phase-locked loop, and K represent the damping ratio. PLL Z represents the equivalent gain coefficient. inv,PLL (s) represents the intermediate frequency phase-locked loop impedance; L f ω represents the inverter output filter inductance. c Z represents the equivalent bandwidth of the inner current loop. inv,H (s) represents the impedance of the high-frequency filter;

[0112] The equivalent impedance transfer function on the power grid side is:

[0113] Z grid (s)=R g +sL g

[0114] Among them, R g L represents the equivalent damping resistance of the power grid. g This represents the equivalent inductance.

[0115] In this embodiment, the output impedance model of the photovoltaic grid-connected inverter can be divided into three parts according to frequency band: the low-frequency band is mainly affected by active power control and can be equivalent to a first-order negative impedance model; the mid-frequency band is dominated by PLL (Phase-Locked Loop) dynamics and can be represented as a second-order damped system; the high-frequency band is dominated by the inverter output filter and current loop control, exhibiting inductive impedance characteristics. By smoothly splicing the above frequency band sub-models at the corresponding bandwidth boundaries, a complete inverter output impedance transfer function Z can be formed. inv (s). The inverter output impedance can be approximated using the following formula:

[0116] Low-frequency negative impedance model: Where R f >0 indicates the magnitude of the equivalent negative impedance, T f This is the time constant under the influence of external active power control. This term provides an approximately constant negative resistance characteristic at very low frequencies, with a real part that is negative, potentially "injecting energy" into the power grid.

[0117] Intermediate frequency PLL model: This second-order element may introduce phase lag or even negative impedance effects near the PLL bandwidth. When the PLL parameters are not appropriate, impedance dips or peaks may occur in the subsynchronous frequency band.

[0118] High-frequency filter model: This section demonstrates that the inverter's output impedance beyond the current loop bandwidth is primarily determined by the output inductance, approximating as the pure inductive reactance jωL. f It exhibits a +90° phase at high frequencies.

[0119] By adding the impedance models for the low, medium, and high frequency bands above, the complete inverter output impedance transfer function can be obtained:

[0120] Z inv (s)≈Z inv,L (s)+Z inv,PLL (s)+Z inv,H (s).

[0121] By adjusting various parameters (such as R) f ,ω PLL ,ω c The above model can fit the measured sweep impedance curves of the inverter under different operating conditions. In this embodiment, model parameters were identified for the 0.5 pu (Per Unit) operating condition. The obtained transfer function in the 38–40 Hz frequency band matches the sweep results in Table 1, verifying the model accuracy.

[0122] Grid-side impedance Z grid(s)It can be calculated based on the short-circuit capacity at the grid connection point and the equivalent network parameters. Generally, the equivalent impedance of the power grid can be expressed in the form of series impedance:

[0123] Z grid (s)=R g +sL g ,

[0124] When the short-circuit ratio of the upstream power grid is not high, such as in a weak power grid scenario, R g Typically much smaller than ωL g Therefore, the power grid impedance is approximately inductively reactant, i.e., Z grid (s)≈jωL g Based on the data from this operating condition, if |Z| is at 39Hz... grid If |≈3.8Ω and the phase angle is approximately 78.7°, then R can be calculated. g ≈0.8Ω, L g ≈0.015H (corresponding to a grid short-circuit capacity that is several tens of times greater than the photovoltaic capacity). Substituting this equivalent parameter into the above model yields the Z value for the entire frequency band. grid (s) characteristic curve.

[0125] Z was obtained inv (s) and Z grid The analytical model of (s) can be used to further calculate the loop transfer function L(s) = Z. grid (s) / Z inv The frequency domain response of L(jω) is used to quickly assess the system's stability margin. By solving for the distance between L(jω) and the -1 point, more accurate gain and phase margin indices can be obtained without relying on point-by-point frequency sweeping. The model analysis results are consistent with the aforementioned direct frequency sweeping calculation results, both indicating that the 38–40 Hz system under 0.5 pu conditions has good stability margin.

[0126] Step 3: Small Perturbation Simulation Verification. To verify the correctness of the frequency domain impedance analysis, this embodiment performed a time-domain small perturbation simulation on a simulation platform. The simulation analysis steps include model building, perturbation injection, simulation execution, data recording, and result analysis.

[0127] (1) Build a photovoltaic power station-level RTDS simulation model;

[0128] (2) Introduce small disturbances into the simulation model (e.g., superimpose a small voltage step at the grid connection point);

[0129] (3) Run electromagnetic transient simulation and record response data such as grid connection point voltage, current and inverter output power;

[0130] (4) Analyze the response waveform, extract the oscillation frequency and attenuation ratio, and compare the results with the stability margin predicted by the frequency domain impedance method to verify them.

[0131] Establish a simulation system corresponding to the equivalent model of actual renewable energy power plants, including modules such as the equivalent upstream power grid, the power plant's main transformer, the photovoltaic inverter cluster, and its controller. For example... Figure 6 The diagram shown is a structural block diagram of the simulation model, which includes modules such as disturbance injection, measurement, controller, and grid connection point, as well as the connection relationships between each part.

[0132] Figure 6 The simulation model includes an equivalent model of the upstream power grid, a photovoltaic inverter and its controller, which are connected through a grid connection point. A small disturbance (such as a voltage step) is introduced at the grid connection point to stimulate the system's dynamic response, and the voltage and current signals at the grid connection point are acquired by a measurement module and sent to the controller for analysis.

[0133] After the simulation model was built, a step disturbance with an amplitude of 0.01 pu was superimposed on the grid connection point voltage by controlling the disturbance module to stimulate the transient response of the new energy power plant grid-connected system. The time-domain waveforms of the three-phase voltage, current, and inverter active power output at the grid connection point were recorded.

[0134] Simulation results reference Figure 7 Simulation results show that after the disturbance is introduced, a small oscillation component with a frequency of approximately 39Hz appears in the grid connection point voltage and inverter current. However, the oscillation amplitude decays rapidly over time, subsiding within about 0.5 seconds, and the system returns to steady state. Spectrum analysis shows that this oscillation frequency matches the 38–40Hz risk band identified in the aforementioned impedance analysis. However, due to sufficient damping in the system, i.e., ample margin, the oscillation at this frequency does not amplify into instability. This dynamic response characteristic is consistent with the conclusion of the frequency domain margin analysis, namely, that under the current control parameters and grid connection capacity, there is no risk of subsynchronous oscillation instability in new energy power plants. By comparing the simulation waveforms with the frequency domain analysis results, the effectiveness and accuracy of the impedance sweep frequency method for evaluating system stability margin are verified.

[0135] Step 4: Suggestions for expanding and optimizing grid-connected capacity.

[0136] In practical applications, the scale of renewable energy power plants may further expand. To assess the impact of grid-connected capacity growth on system stability, this embodiment conducts a capacity expansion simulation study based on the above model. By increasing the equivalent number of inverters in the RTDS simulation, the total grid-connected capacity of the renewable energy power plant is gradually increased from 60MW to 100MW, and the number of inverters is increased from 60 to 100 equivalent units. As more inverters are connected in parallel, the equivalent output impedance Z of the inverter cluster increases. inv The impedance will decrease proportionally to the parallel connection, approximating as 1 / n of the output impedance of a single inverter. Correspondingly, the loop transfer function L(jω) = Z grid / Z invThe amplitude will increase, the Nyquist trajectory will be closer to the (-1,0) critical point, and the stability margin will show a decreasing trend.

[0137] Simulation results show that as the grid-connected capacity increases, the system gain margin in the 38–40Hz frequency band gradually decreases from the original 20dB, and the Nyquist curves for each operating condition gradually approach -1. When the total grid-connected capacity approaches 100MW, the margin decreases significantly, approaching the stability critical point. This means that the previously safe frequency band may trigger broadband oscillations under larger-scale grid connections, which requires attention. To address this trend, this embodiment can improve the stability margin by optimizing control parameters. The optimization strategy is as follows:

[0138] Reduce PLL bandwidth: Appropriately reduce the bandwidth of the inverter's phase-locked loop to decrease its sensitivity to subsynchronous frequency band disturbances. After reducing the PLL bandwidth, the negative impedance effect of the inverter in the 20–50Hz range is weakened, which can improve the damping in this frequency band and obtain a larger phase margin than the original control strategy.

[0139] Adjusting current loop parameters: Optimize the inverter's inner current loop PI regulator to reduce the peak impedance amplitude in the high-frequency range (>100Hz). Appropriately reducing the proportional gain of the current loop or improving the filter stage can weaken the resonance peaks generated in the mid-to-high frequencies, helping to avoid the risk of high-frequency broadband oscillations.

[0140] Enhanced damping control: An additional damping control element is introduced into the inverter control (a differential damping term is added to the grid connection point voltage disturbance observation) to offset the damping decrease caused by the increase in the number of parallel inverters. This ensures that the overall system damping ratio does not become too low when the grid-connected capacity increases, thereby maintaining sufficient stability margin.

[0141] Through the comprehensive application of the above measures, simulation monitoring shows that when the photovoltaic power station is expanded to 100MW, the system's gain margin and phase margin are maintained within a safe range, avoiding potential oscillations and instability. Therefore, the new energy power station grid-connected system expansion calculation method provided in this embodiment can assess the system's stability margin evolution trend in advance for different operating conditions and capacity scales, and guide the optimization of control parameters to ensure stable operation of large-scale grid connection.

[0142] In one possible implementation, after constructing a simulation model of a new energy power plant grid-connected system with an adjustable number of inverters connected in parallel, the method provided in this embodiment further includes:

[0143] The optimization objectives are to maximize the stability margin of the simulation model and minimize the dynamic performance parameters. The particle swarm optimization algorithm is used to optimize the control parameters of the simulation model and determine the optimal solution set of the control parameters. The control parameters include phase-locked loop parameters, current loop parameters, and outer loop control parameters. The dynamic performance parameters include overshoot and dynamic response time.

[0144] This embodiment allows for parameter tuning based on margin analysis. Control parameters are tuned through quantitative stability margin analysis, specifically by using frequency domain metrics such as phase margin and gain margin to assess system stability. Phase margin can be defined as the margin of the open-loop transfer function at the unity-gain crossover frequency, with a phase distance of -180°, expressed as: Φ m =180°+∠L(jω0), where ω0 is the frequency at which the open-loop gain is 1. The gain margin is the reciprocal of the open-loop gain when the phase is -180°, usually expressed in decibels, such as... The greater the margin, the further the system is from instability, and the higher its robustness.

[0145] Specifically, the implementation process of the parameter tuning method is as follows:

[0146] a. Model Establishment and Margin Calculation: First, establish a typical small-signal transfer function model of a photovoltaic grid-connected inverter, including the phase-locked loop (PLL) and the inner-loop PI controller. Calculate the phase margin and gain margin of the system under baseline parameters. Read the margin values ​​using an open-loop Bode plot. Ensure sufficient but not excessive stability margins under the baseline design (e.g., phase margin > 40°, gain margin > 6dB).

[0147] b. Parameter Sensitivity Analysis: Key control parameters were varied and the stability margin was recalculated on a typical small-signal transfer function model of a photovoltaic grid-connected inverter. The impact of each parameter on the margin was quantitatively evaluated. Key control parameters included PLL bandwidth (i.e., the natural frequency of the PLL controller) and current loop PI control parameters (such as proportional gain K). p Record the curves showing the phase margin changing with parameters. For example, gradually increase the PLL bandwidth from 30Hz to 60Hz and observe the decreasing trend of the phase margin; increase the current loop proportional gain from 0.5 to 2.0 and record the change in phase margin. Evaluate which parameters are most sensitive to the phase margin by analyzing the slope of the curves.

[0148] c. Determine key control parameters and optimize strategies: Based on the sensitivity analysis results, identify the parameters that have the greatest impact on stability margin. PLL bandwidth is typically a crucial factor; under weak grid conditions, excessively high PLL bandwidth can significantly reduce stability margin, causing phase differences as high as 270°, which can easily lead to system instability. Appropriately reducing the PLL bandwidth can increase low-frequency damping and improve stability margin. Current loop gain is also an influencing factor—excessive gain will introduce a "negative damping" characteristic at the grid connection point, reducing the system phase angle margin; appropriately reducing the current loop PI gain can improve damping margin. Therefore, the optimization strategy should prioritize adjusting margin-sensitive parameters, such as reducing the PLL loop bandwidth and moderately reducing the current loop PI gain, to gain more stability margin.

[0149] d. Verify Performance Impact: While improving the margin, evaluate the impact of these key control parameter adjustments on dynamic performance parameters (such as transient overshoot, response time, etc.). Generally, reducing the PLL bandwidth and current loop gain can improve the stability margin, but at the cost of some dynamic response speed. This embodiment uses simulation to obtain the impact curves of each control parameter change on margin and performance, and finds the balance point. For example, in a simulation, reducing the PLL bandwidth from 30Hz to 20Hz increases the phase margin from approximately 60° to 70°, but extends the voltage recovery time from 0.2s to 0.3s; reducing the current loop proportional gain from 2.0 to 1.0 increases the margin by approximately 15°, but slightly increases the steady-state error. Record these results to guide tuning.

[0150] To address the often trade-off between stability margin and dynamic performance, this embodiment introduces a multi-objective optimization method to maximize dynamic performance while meeting the minimum stability margin requirement. The algorithm uses the stability margin M (e.g., phase margin or eigenvalue damping ratio) and performance metrics P (e.g., response speed, a function of overshoot) as two optimization objectives, constructing a "dual-objective" optimization problem. For example, requiring a phase margin of at least 30° and minimizing voltage recovery time can be expressed as: ... (The last part, "M(p) ≥ M...", appears to be an incomplete sentence or fragment.) min Under constraints, optimize the control parameter vector p, which includes PLL bandwidth and PI gain, to maximize the stability margin and minimize the dynamic performance parameter P(p). Where M... min This is the minimum requirement for stability margin (e.g., a phase margin of 30°).

[0151] Since it is difficult for the two optimization objectives to be optimal at the same time, this embodiment can use the weighting method or Pareto optimal solution set to solve for the optimal solution of the control parameters.

[0152] Specifically, when optimizing control parameters, the minimum stability margin M is first set according to the design requirements. min For example, M min The angle can be 30° to 50°. Preferably, M... minThe value is 30°, and the dynamic performance parameter P is evaluated. The set of control parameters that need to be optimized is clearly defined, including the PLL loop bandwidth ω. PLL Current PI gain (K p ,K i (e.g., ), and their respective allowed value ranges.

[0153] Secondly, using the aforementioned margin analysis results, sensitivity curves of each control parameter to stability margin and dynamic performance parameters are obtained. For example, the influence curves of PLL bandwidth on phase margin and voltage transient overshoot are plotted; the influence curves of current loop PI gain on stability margin and current response time are plotted, etc. These margin-performance sensitivity curves determine the magnitude of the "gain" of parameter changes to the two objectives, guiding the optimization search direction.

[0154] Then, in this embodiment, the problem is formalized into a multi-objective optimization model. Weights are selected (or Lagrange multipliers are introduced) to merge the two objectives into a single objective function J(p) = w·M(p) + (1-w)·P(p) for solution; or the Pareto front method is directly used: by scanning the parameter space, the set of unmanageable solutions is obtained, that is, the set of parameter combinations that cannot be improved on one objective but do not degenerate on the other objective.

[0155] By traversing the parameter space using simulation or algorithms (such as particle swarm optimization, genetic algorithms, etc.), we can find the parameter that satisfies M ≥ M. min The Pareto optimal solution.

[0156] Extracting three parameter ranges: Select solutions representing three different weighting options and provide the corresponding tuning ranges for the control parameters. The three weighting options include:

[0157] 1. Optimal Approach to Dynamic Performance Parameters: Emphasizing dynamic performance while meeting the minimum margin M min This is the solution that maximizes performance indicators under the premise of [specific conditions]. This parameter is usually taken as the upper limit of the control bandwidth, such as when the PLL bandwidth is high (e.g., close to 60Hz), and the current loop K [value is used]. p It is relatively large, with the shortest dynamic response time, but its stability margin is only slightly higher than M. min .

[0158] 2. Compromise-Balanced Approach: A scheme that achieves a balance between stability margin and dynamic performance parameters. Control parameters are set to moderately biased values, such as moderate PLL bandwidth and moderate current loop gain. Under this scheme, the system phase margin and dynamic response time are both at moderate levels, representing a "suboptimal" tuning that compromises between the two.

[0159] 3. Conservative Stability Approach: This approach prioritizes stability margin. Control parameters are chosen conservatively to maximize stability margin, such as reducing the PLL bandwidth to the lower limit, appropriately decreasing the proportional gain of the current loop, and adding additional damping components (such as parallel resistors or hysteresis compensators) if necessary to improve damping in specific frequency bands. This scheme provides sufficient phase margin, but the dynamic response time is relatively long.

[0160] The three parameter schemes were tested in a simulation model to observe whether the dynamic response time and stability margin met the design expectations. For example, grid-connection disturbances were applied to a typical renewable energy power plant grid-connected system to verify that the "optimal dynamic performance parameter orientation" resulted in the fastest transient recovery time for current and voltage, but slight steady-state oscillations; the "conservative stability orientation" provided sufficient oscillation margin but a slower response; and the "compromise and balance orientation" offered a balanced approach in all aspects. The parameter range boundaries were fine-tuned based on the simulation results to ensure that each scheme had a certain margin in its practical application, facilitating selection and deployment according to different engineering needs.

[0161] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0162] The following are device embodiments of the present invention. For details not described in detail, please refer to the corresponding method embodiments described above.

[0163] This invention provides a stability margin calculation device for a new energy power plant grid-connected system. For ease of explanation, only the parts relevant to this invention are shown, and are detailed below:

[0164] The stability margin calculation device for the grid-connected system of new energy power plants includes:

[0165] An impedance acquisition module is used to acquire the inverter output impedance and grid-side equivalent impedance of the initial renewable energy power plant grid-connected system under multiple operating conditions; the initial renewable energy power plant grid-connected system includes one inverter.

[0166] The stability margin calculation module is used to take the ratio of the inverter output impedance to the grid-side equivalent impedance under the same operating condition as the open-loop transfer function, and based on the open-loop transfer function under each operating condition, determine the gain margin and phase margin of the new energy power station grid-connected system under each operating condition.

[0167] The weakest operating condition selection module is used to determine the weakest operating condition of the new energy power station grid connection system based on the gain margin and phase margin of the new energy power station grid connection system under various operating conditions.

[0168] The maximum expansion capacity determination module is used to determine the maximum number of inverters that can be expanded in the grid-connected system of the new energy power station under the weakest operating condition, based on the gain margin and phase margin of the grid-connected system of the new energy power station with different numbers of inverters connected in parallel.

[0169] In one possible implementation, the impedance acquisition module includes:

[0170] The inverter output impedance and grid-side equivalent impedance of the new energy power station grid-connected system under various operating conditions are obtained by the frequency sweep perturbation method.

[0171] In one possible implementation, the stability margin calculation module includes:

[0172] Plot the Nyquist curves of the open-loop transfer function under various operating conditions;

[0173] For any Nyquist curve corresponding to any operating condition, the difference between the phase of the intersection point of the Nyquist curve and the unit circle and the first preset phase is taken as the phase margin of the operating condition; and the point in the Nyquist curve with the first preset phase is taken as the first target point, and the distance between the first target point and the critical reference point is taken as the gain margin.

[0174] In one possible implementation, the weakest condition selection module includes:

[0175] The stability margin is obtained by weighted summation of the gain margin and the phase margin.

[0176] The operating condition with the smallest stability margin is taken as the weakest operating condition of the new energy power station grid connection system.

[0177] In one possible implementation, the maximum expansion capacity determination module includes:

[0178] Multiple scenario margin calculation units are used to gradually increase the number of inverters connected in parallel in the new energy power station grid-connected system, and to calculate the gain margin and phase margin of the new energy grid-connected system under different numbers of inverters connected in parallel.

[0179] The maximum expansion capacity determination unit is used to determine the maximum number of inverters connected in parallel with a gain margin and a phase margin not less than the corresponding margin threshold as the maximum expansion capacity of the new energy power station grid-connected system.

[0180] In one possible implementation, the multiple scene margin calculation units include:

[0181] Based on formula Z inveq (s)=Z inv(s) / n calculates the inverter output impedance of the new energy grid-connected system under different numbers of inverters connected in parallel; and uses the initial grid-side equivalent impedance of the new energy power plant grid-connected system as the grid-side equivalent impedance of the new energy grid-connected system under different numbers of inverters connected in parallel; where, Z inveq (s) represents the inverter output impedance of the new energy grid-connected system when the number of inverters connected in parallel is n, Z inv (s) represents the initial inverter output impedance of the new energy power station grid-connected system; n represents the number of inverters connected in parallel; the ratio of the inverter output impedance to the grid-side equivalent impedance under the weakest operating condition is used as the open-loop transfer function.

[0182] Based on the open-loop transfer function of the weakest operating condition, the gain margin of the new energy power station grid-connected system under the weakest operating condition is determined.

[0183] In one possible implementation, the apparatus provided in this embodiment further includes a simulation verification module, used for:

[0184] A simulation model of a new energy power plant grid-connected system with an adjustable number of inverters in parallel is constructed. The simulation model includes a new energy power plant simulation model with an adjustable number of inverters in parallel, a grid-side simulation model, and a grid connection point simulation model.

[0185] Set the parameters corresponding to the weakest working condition to the simulation model, and apply a disturbance signal to the simulation model;

[0186] Run the simulation model and gradually increase the number of inverters connected in parallel. For each number of inverters connected in parallel, collect the grid connection point electrical signal of the simulation model under that number of inverters connected in parallel. Extract the dynamic performance parameters of the simulation model based on the grid connection point electrical signal, and determine whether the simulation model remains stable under that number of inverters connected in parallel based on the dynamic performance parameters.

[0187] If the simulation model remains stable at the maximum number of units expanded, and the simulation model becomes unstable at the first preset number of units expanded, then the maximum number of units expanded is determined as the critical value for the number of inverters expanded in the grid-connected system of the new energy power station; the first preset number of units is the value obtained by adding one to the maximum number of units expanded.

[0188] In one possible implementation, the apparatus provided in this embodiment further includes a control parameter tuning module, used for:

[0189] The optimization objectives are to maximize the stability margin of the simulation model and minimize the dynamic performance parameters. The particle swarm optimization algorithm is used to optimize the control parameters of the simulation model and determine the optimal solution set of the control parameters. The control parameters include phase-locked loop parameters, current loop parameters, and outer loop control parameters. The dynamic performance parameters include overshoot and dynamic response time.

[0190] This embodiment provides a terminal, including: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps in the above embodiments of the stability margin calculation methods for various renewable energy power plant grid-connected systems, for example... Figure 1 Steps S101 to S104 are shown. Alternatively, when the processor executes the computer program, it implements the functions of each module / unit in the above-described device embodiments.

[0191] For example, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the terminal.

[0192] The terminal can be a computing device such as a desktop computer, laptop, handheld computer, or cloud server. The terminal may include, but is not limited to, a processor and memory. The terminal may also include input / output devices, network access devices, and a bus.

[0193] The processor referred to can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0194] The memory can be an internal storage unit of the terminal, such as the terminal's hard drive or RAM. The memory can also be an external storage device of the terminal, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory can include both internal and external storage units. The memory is used to store the computer program and other programs and data required by the terminal. The memory can also be used to temporarily store data that has been output or will be output.

[0195] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0196] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0197] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0198] In the embodiments provided by this invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0199] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0200] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0201] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium. When executed by a processor, the computer program can implement the steps of the stability margin calculation method embodiments for each of the above-mentioned new energy power station grid-connected systems. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0202] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for calculating the stability margin of a new energy power plant grid-connected system, characterized in that, include: Obtain the inverter output impedance and grid-side equivalent impedance of the initial new energy power plant grid-connected system under multiple operating conditions; The initial new energy power station grid connection system includes one inverter; The ratio of the inverter output impedance to the grid-side equivalent impedance under the same operating condition is used as the open-loop transfer function. Based on the open-loop transfer function under each operating condition, the gain margin and phase margin of the new energy power station grid-connected system under each operating condition are determined. Based on the gain margin and phase margin of the new energy power station grid connection system under various operating conditions, the weakest operating condition of the new energy power station grid connection system is determined. Under the weakest operating condition, based on the gain margin and phase margin of the grid-connected system of the new energy power station with different numbers of inverters connected in parallel, the maximum number of inverters that can be expanded to support the grid-connected system of the new energy power station is determined.

2. The method for calculating the stability margin of a new energy power station grid-connected system according to claim 1, characterized in that, The acquisition of inverter output impedance and grid-side equivalent impedance of the new energy power plant grid-connected system under multiple operating conditions includes: The inverter output impedance and grid-side equivalent impedance of the new energy power station grid-connected system under various operating conditions are obtained by the frequency sweep perturbation method.

3. The method for calculating the stability margin of a new energy power station grid-connected system according to claim 1, characterized in that, The determination of the gain margin and phase margin of the new energy power station grid-connected system under various operating conditions, based on the open-loop transfer function under each operating condition, includes: Plot the Nyquist curves of the open-loop transfer function under various operating conditions; For any Nyquist curve corresponding to any operating condition, the difference between the phase of the intersection point of the Nyquist curve and the unit circle and the first preset phase is taken as the phase margin of the operating condition; and the point in the Nyquist curve with the first preset phase is taken as the first target point, and the distance between the first target point and the critical reference point is taken as the gain margin.

4. The method for calculating the stability margin of a new energy power station grid-connected system according to claim 1, characterized in that, The determination of the weakest operating condition of the new energy power station grid-connected system based on the gain margin and phase margin under various operating conditions includes: The stability margin is obtained by weighted summation of the gain margin and the phase margin. The operating condition with the smallest stability margin is taken as the weakest operating condition of the new energy power station grid connection system.

5. The method for calculating the stability margin of a new energy power station grid-connected system according to claim 1, characterized in that, The determination of the maximum number of inverters that can be expanded in the grid-connected system of the new energy power station, based on the gain margin and phase margin of the grid-connected system of the new energy power station under different numbers of inverters connected in parallel, includes: Gradually increase the number of inverters connected in parallel in the new energy power plant grid-connected system, and calculate the gain margin and phase margin of the new energy grid-connected system under different numbers of inverters connected in parallel; The maximum number of inverters connected in parallel with a gain margin and a phase margin not less than the corresponding margin threshold is taken as the maximum number of inverters that can be expanded in the grid-connected system of the new energy power station.

6. The method for calculating the stability margin of a new energy power station grid-connected system according to claim 5, characterized in that, The calculation of the gain margin of the new energy grid-connected system under different numbers of inverters connected in parallel includes: Based on formula Z inveq (s)=Z inv (s) / n calculates the inverter output impedance of the new energy grid-connected system under different numbers of inverters connected in parallel; and uses the initial grid-side equivalent impedance of the new energy power plant grid-connected system as the grid-side equivalent impedance of the new energy grid-connected system under different numbers of inverters connected in parallel; where, Z inveq (s) represents the inverter output impedance of the new energy grid-connected system when the number of inverters connected in parallel is n, Z inv (s) represents the initial inverter output impedance of the new energy power station grid-connected system; n represents the number of inverters connected in parallel; The ratio of the inverter output impedance to the grid-side equivalent impedance under the weakest operating condition is used as the open-loop transfer function. Based on the open-loop transfer function of the weakest operating condition, the gain margin of the new energy power station grid-connected system under the weakest operating condition is determined.

7. The method for calculating the stability margin of a new energy power station grid-connected system according to claim 1, characterized in that, After determining the maximum number of inverters that can be expanded in the grid-connected system of the new energy power station based on the gain margin and phase margin of the grid-connected system of the new energy power station under different numbers of inverters connected in parallel, the method further includes: A simulation model of a new energy power plant grid-connected system with an adjustable number of inverters in parallel is constructed. The simulation model includes a new energy power plant simulation model with an adjustable number of inverters in parallel, a grid-side simulation model, and a grid connection point simulation model. Set the parameters corresponding to the weakest working condition to the simulation model, and apply a disturbance signal to the simulation model; Run the simulation model and gradually increase the number of inverters connected in parallel. For each number of inverters connected in parallel, collect the grid connection point electrical signal of the simulation model under that number of inverters connected in parallel. Extract the dynamic performance parameters of the simulation model based on the grid connection point electrical signal, and determine whether the simulation model remains stable under that number of inverters connected in parallel based on the dynamic performance parameters. If the simulation model remains stable at the maximum number of units expanded, and the simulation model becomes unstable at the first preset number of units expanded, then the maximum number of units expanded is determined as the critical value for the number of inverters expanded in the grid-connected system of the new energy power station; the first preset number of units is the value obtained by adding one to the maximum number of units expanded.

8. The method for calculating the stability margin of a new energy power station grid-connected system according to claim 7, characterized in that, After constructing the simulation model of the new energy power plant grid-connected system with an adjustable number of inverters in parallel, the method further includes: The optimization objectives are to maximize the stability margin of the simulation model and minimize the dynamic performance parameters. The particle swarm optimization algorithm is used to optimize the control parameters of the simulation model and determine the optimal solution set of the control parameters. The control parameters include phase-locked loop parameters, current loop parameters, and outer loop control parameters. The dynamic performance parameters include overshoot and dynamic response time.

9. A terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the stability margin calculation method for the grid-connected system of a new energy power station as described in any one of claims 1 to 8.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the stability margin calculation method for the grid-connected system of the new energy power station as described in any one of claims 1 to 8.

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