A method for matching the capacity of a grid-connected station with a grid-constructed network and a new energy grid-connected system

Abstract

The application discloses a kind of follow network mixed-connection station capacity matching method and system, belong to high proportion new energy grid-connected stability analysis and converter capacity planning technical field;Including: the positive sequence port impedance model of establishing follow network type and network type inverter;Definition network type inverter rated capacity proportion k, and with k and (1-k) as capacity weight to the parallel aggregation of two kinds of port admittance, establish mixed-connection station total equivalent output impedance;In the setting analysis frequency band, the minimum value of the real part of total equivalent output impedance is defined as the system passive margin PM (k);Iterate capacity proportion and output minimum k as network type inverter minimum rated capacity proportion, which satisfies PM (k) ≥0.The application directly introduces the frequency related control dynamics of two kinds of converters into capacity matching criterion, and the minimum network capacity boundary can be quantified without repeatedly building complete time-domain model for each candidate capacity.

Description

Technical Field

[0001] This invention belongs to the technical field of high-proportion renewable energy grid connection stability analysis and converter capacity planning, specifically involving a capacity allocation method for hybrid power plants connected to the grid and a renewable energy grid connection system. Background Technology

[0002] With the large-scale integration of new energy sources such as wind power and photovoltaics via power electronic converters, especially in scenarios involving large-scale new energy bases in barren deserts, long-distance power transmission, and areas lacking synchronous power supply support, the equivalent impedance of the AC grid increases, short-circuit capacity decreases, and grid strength at the point of common coupling (PCC) declines. Grid-following (GFL) converters typically rely on phase-locked loops (PLLs) for grid synchronization. The coupling between their PLLs, current control loops, and external grid impedance can introduce negative damping and induce subsynchronous, low-frequency, or other broadband oscillations under weak grid conditions. Grid-forming (GFM) converters can actively establish or support AC side voltage and frequency through voltage source control, exhibiting better synchronization and voltage support capabilities under weak grid conditions; however, the oscillation stability of GFM converters is still related to grid strength, control parameters, operating point, and interactions among multiple converters. In some strong grids or parameter combinations, low-frequency stability margins may also decrease. Therefore, the mixed configuration of GFL and GFM units within the same new energy power station has become an important technical approach that balances stability support capabilities, utilization of existing equipment, and scale of engineering upgrades.

[0003] For power plants integrated with the grid, the engineering problem is not simply increasing the proportion of GFM (Gateway Flow Meter) units, but rather determining the minimum rated capacity proportion of GFM units that can meet the target oscillation frequency band stability requirements, given main circuit parameters, control parameters, and grid conditions. Adding new GFM units or upgrading them for grid integration typically involves engineering investments such as control system modifications, energy storage or DC-side energy resource allocation, overcurrent capacity design, and equipment investment. If the GFM capacity is too small, it is difficult to obtain the required stability margin; if it is too large, it may result in unnecessary grid integration. Therefore, developing a quantitative method that can directly calculate the "minimum feasible grid capacity" from the equipment frequency characteristics has clear engineering significance for the planning and upgrading of new energy power plants.

[0004] Regarding control mode adaptation, existing research paper "Impedance Adaptive Dual-Mode Control of Grid-Connected Inverters With Large Fluctuation of SCR and Its Stability Analysis Based on D-Partition Method" (IEEE Transactions on Power Electronics, 2021, 36(12): 14420-14435, DOI: 10.1109 / TPEL.2021.3087028) proposes impedance adaptive dual-mode control for large-range fluctuations in short-circuit ratio and uses the D-partition method to analyze the stability domain. The main purpose of this type of scheme is to adjust the control operation mode of a single converter according to the grid conditions. Its technical object and output results are different from the determination of the lower limit of GFM installed capacity at the plant level, and it cannot directly give the minimum rated GFM capacity required to meet the stability constraints under a given GFL / GFM control structure.

[0005] In the research on grid strength-based capacity allocation, Xin Huanhai et al. published "Estimation of Grid-Forming Converter Capacity Allocation to Improve the Stability of New Energy Power Stations" in the Proceedings of the CSEE, Vol. 44, No. 14, 2024, pp. 5463-5473. They studied the GFM / GFL capacity allocation from the perspective of generalized short-circuit ratio (gSCR) and small-signal stability margin. Xin et al. published "How Many Grid-Forming Converters Do We Need? A Perspective From SmallSignal Stability and Power Grid Strength" in IEEE Transactions on Power Systems, 2025, 40(1): 623-635 (DOI: 10.1109 / TPWRS.2024.3393877), further establishing the relationship between GFM capacity ratio and equivalent grid strength and stability margin. The above methods provide an important basis for capacity estimation, but their core constraints are mainly characterized by SCR / gSCR type grid strength indicators. For frequency-related port dynamics caused by control links such as PLL, voltage loop, current loop, and droop loop, it is necessary to indirectly reflect them through additional models or critical indicators.

[0006] Regarding state-space and modal methods, Zhang Bin, Zhang Xueguang, and Xu Dianguo published "Analysis of Key Influencing Factors on the Matching Ratio of Hybrid Grid-connected Systems with Grid-connected and Connected Converters" in the journal *Automation of Electric Power Systems*, Vol. 49, No. 1, 2025. This study investigated the influence of control parameters and voltage loop structure on the lower limit of the GFM matching ratio using a state-space model. Yu Guangzheng, Hu Yue, Liu Chenxi, et al. published "Coordinated Optimization Configuration Method for Hybrid Multi-Infeed Systems with Grid-connected / Grid-connected Converters" (DOI: 10.13334 / j.0258-8013.pcsee.231143) in the journal *Proceedings of the Chinese Society for Electrical Engineering*, Vol. 45, No. 2, 2025 (pp. 588-601). This study employed modal analysis and modal decoupling approximation to establish multi-band support capability indices and perform coordinated optimization configuration. This type of method can obtain rich modal information, but it usually requires the establishment of a higher-order state-space model, the calculation of eigenvalues, or the performance of multivariate optimization. When the equipment control parameters, operating mode, or equivalent model of the station change, it is often necessary to reconstruct or update the corresponding system matrix.

[0007] In the area of ​​frequency domain impedance analysis, Wang et al. published “Control interaction analysis of hybrid system with grid-following and grid-forming inverters based on admittance decomposition” (Article 110267, DOI: 10.1016 / j.ijepes.2024.110267) in the International Journal of Electrical Power & Energy Systems, Volume 162, 2024, using admittance decomposition to analyze the multi-timescale control interaction between GFL and GFM and construct a stable and secure domain. Ni et al. published “Modular Impedance Modeling and Stability Analysis of Hybrid AC / DC Power Systems With Grid-Forming and Grid-Following Converters” (DOI: 10.1109 / ACCESS.2023.3348784) in IEEE Access, Volume 12, 2024, pp. 4063-4077, establishing a modular three-port admittance model and frequency domain stability criteria, and discussing the impact of different GFM capacity ratios on system stability. The above studies demonstrate that the impedance / admittance method is suitable for describing the frequency coupling between different controllers and the power grid. However, its focus is on stability assessment, interaction mechanism, or capacity ratio change trend. It does not directly form a scalar margin using the "most unfavorable frequency real part" of the total equivalent output impedance of the hybrid power station as the scalar margin and using this margin to inversely calculate the minimum GFM capacity ratio.

[0008] The passive impedance theory provides another basis for the aforementioned quantitative constraints in the frequency domain. Du Xiaheng, He Yuying, Zou Wen, et al., published "A Review of Impedance Passivity Methods for Grid-Connected and Grid-Mounted Inverters" (DOI: 10.19718 / j.issn.1005-2992.2024-02-0012-09) in the *Journal of Northeast Electric Power University*, Vol. 44, No. 2, 2024, pp. 12-20, pointing out that the passive impedance of grid-connected inverter ports can serve as a sufficient condition for ensuring the stability of grid-connected power generation systems, and systematically summarizes methods for achieving passive impedance through controller optimization, virtual impedance, etc. Existing passive impedance research mainly focuses on "how to modify the control of a single unit or a single type of converter to improve its impedance," and cannot be equated with the site planning problem of "how much GFM rated capacity should be configured under given two types of controller parameters."

[0009] Patent document CN117498443B, "A Method and System for Active Power Coordination Optimization Control of Grid-connected and Grid-connected Converters," establishes a small-signal state-space model to obtain the relationship between the output power ratio and the damping ratio of the dominant oscillation mode, and uses an intelligent optimization algorithm to obtain the optimal output power ratio with the goal of maximizing the damping ratio. Patent document CN118589473B, "An Optimal Ratio and Layout Design Method and Related Devices for Grid-connected and Grid-connected Converters in a 100% New Energy Multi-Machine System," constructs the relationship between the converter distribution matrix and the robust stability margin to find the proportion of GFM / GFL quantities, power ratios, and layout schemes with larger stability margins. Patent document CN120150239B, "A Capacity Ratio Method for Grid-connected and Grid-connected Converters Based on Semidefinite Programming," uses a station state-space model, Lyapunov semidefinite programming, and stability sensitivity iteration to obtain the ratio of grid-connected converters. The aforementioned patents all indicate that "ratio optimization" itself has been disclosed, and its main criteria are based on state-space characteristic modes, robust stability margin, or semidefinite programming stability index, which is different from the technical route of directly determining the minimum capacity boundary based on the passive margin of port impedance.

[0010] Furthermore, patent document CN119093414B, "Method, System, Equipment and Medium for Networked Control Retrofitting," determines the retrofitting location using the gSCR influence factor and solves for the minimum networked retrofitting capacity using the extended admittance matrix eigenvalue and critical short-circuit ratio as constraints. Patent document CN119561154B, "A Method and System for Networked Converter Capacity Configuration Based on Short-Circuit Ratio Margin," calculates the required total GFM capacity based on the current short-circuit ratio, critical short-circuit ratio, and target short-circuit ratio margin. While both technologies can provide quantitative capacity results, their core stability constraints remain the SCR / gSCR or its derived eigenvalue / critical short-circuit ratio index, and they do not directly use the minimum real part of the port impedance that simultaneously retains the dynamics of GFL and GFM control as the capacity criterion.

[0011] Another patent document, CN118826133B, entitled "A Dual-Mode Fusion Control Method for Grid-Connected Inverters Based on Passiveness," utilizes a port-controlled Hamiltonian model to construct passive feedback control laws for both grid-connected and grid-connected types and performs weighted fusion. Its passive nature is used for the design of control laws for a single inverter, rather than for GFM capacity planning in hybrid power plants. Another patent document, CN120810766A, entitled "A Stability Analysis Method for Grid-Connected / Grid-Connected Hybrid Power Plants Based on Impedance Model," establishes GFL / GFM sequence impedance and hybrid power plant impedance networks, and analyzes the risk of subsynchronous / supersynchronous oscillations under different GFM connection numbers based on impedance ratio and the Nyquist criterion. This scheme aims at stability risk identification and stability boundary change analysis, but does not use the capacity ratio as an explicit weight for impedance paralleling to further construct a direct mapping of "minimum real part passive margin in the frequency band—minimum feasible capacity ratio."

[0012] The dissertations also studied the combined operation and capacity issues of GFL / GFM from different perspectives. Dr. Liu Pengyin's dissertation at Tsinghua University, "Converter Grid-Connected / Grid-Integrated Combined Control and Its Oscillation Stability Analysis" (2024), investigated the impact of GFM proportion on oscillation frequency and damping, and proposed a capacity optimization configuration method that satisfies full-condition oscillation stability and economic constraints. Dr. Li Shuang's dissertation at the China Electric Power Research Institute, "Small Disturbance Stability Mechanism and Control Technology of Grid-Connected / Grid-Integrated Hybrid Photovoltaic Power Generation System" (2025), analyzed the impact of GFM proportion on the active power output stability domain based on equivalent loop gain. Master's thesis Gou Shaoyun at North China Electric Power University, "Study on Grid-Connected Stability Domain of Grid-Connected and Grid-Connected Hybrid Direct-Drive Wind Farms" (2025), used state-space models and multi-dimensional constrained stability domains to study the stability margin and dominant constraints under different GFM wind turbine proportions. These studies further illustrate a clear correlation between GFM proportion and stability, but its capacity determination usually relies on full-order / equivalent state-space analysis, loop gain analysis, or multi-dimensional stability domain analysis.

[0013] In summary, existing publicly available technologies have formed various technical routes, including SCR / gSCR estimation, state-space / eigenvalue and modal optimization, robust stability and semidefinite programming, impedance / Nyquist stability analysis, and passive control. For the parallel-connected and networked hybrid power stations with the same PCC targeted by this invention, the aforementioned representative publicly available technologies have not yet formed a complete capacity-limited link as follows: retaining the dynamic control of GFL and GFM to establish positive-sequence port impedances respectively; performing capacity-weighted parallel aggregation of the two types of port admittances using the rated capacity ratio of GFM (k) and the rated capacity ratio of GFL (1-k); defining the minimum real part of the total equivalent output impedance of the power station within the target analysis frequency band as the passive margin PM(k); and using PM(k) not less than 0 as the passive stability constraint of the target frequency band, directly searching for the minimum rated capacity ratio of GFM that satisfies this constraint. Therefore, a power station capacity allocation method with a clear model interface, capable of retaining the frequency-related control dynamics of the two types of converters, and directly outputting the minimum network capacity boundary is still needed. Summary of the Invention

[0014] The technical solution of this invention is used to solve the problem of how to directly map the rated capacity ratio of the grid-connected inverter to the passive margin of the frequency domain port impedance of the hybrid power station while retaining the control dynamic characteristics of the grid-connected and grid-based inverters, and thereby obtain the minimum grid-connected capacity ratio that meets the passive stability constraints of the target analysis frequency band. This reduces the model reconstruction and repeated calculation problems caused by relying solely on SCR / gSCR scalar estimation, full-order state-space / eigenvalue optimization, or time-domain simulation trial and error.

[0015] The present invention solves the above-mentioned technical problems through the following technical solutions: This invention provides a method for capacity allocation of hybrid power stations connected to a grid, comprising the following steps: S1. Input the system parameters of the grid inverter, including: main circuit parameters, control parameters, grid parameters and analysis frequency band; S2. Establish the positive sequence impedance models for grid-connected and mesh-type inverters. GFL (s) and Z GFM (s); S3. Under the unified rated capacity benchmark, define the rated capacity ratio of grid-type inverters as k, where k∈[0,1], and the rated capacity ratio of root-type inverters as (1-k); determine the traversal range of k [k1,k2] and set the traversal step size △k, where k1 is the lower limit of the traversal range and k2 is the upper limit of the traversal range. S4. Under a unified rated capacity benchmark, the capacity weighted parallel equivalent of the two types of positive sequence port admittances is performed according to the capacity ratio k of the network type and the capacity ratio (1-k) of the follow-up network type, and the total equivalent output impedance of the station is established. ; S5. Iterate through each capacity percentage k within the range [k1, k2]; S5.1 For the current k, calculate its total equivalent output impedance within the analysis frequency band. Where j is the imaginary unit and ω is the corresponding angular frequency within the analysis band; S5.2, Define the minimum value of the real part of the total equivalent output impedance within the analysis frequency band as the passive margin of the system at the current k. ; S5.3 Margin Judgment: Based on the sufficient condition of passivity, within the analysis frequency band, if PM(k)≥0, record the current k and exit the loop; if PM(k)<0 and k+△k≤k2, let k=k+△k and return to step S5.1 to continue traversing; if PM(k)<0 and k+△k>k2, output the capacity percentage that does not meet the passive margin requirement within the current traversal range and end. S6. Output the smallest k that satisfies PM(k)≥0 under a given traversal range and traversal step size, as the minimum grid-type inverter rated capacity percentage k that satisfies the passive stability constraint of the analysis frequency band. min .

[0016] Furthermore, the positive sequence impedance model of the grid-connected inverter The calculation formula is: ,in, Let be the transfer function of the filter capacitor and its damping resistor. This is the port output impedance transfer function for a grid-connected inverter.

[0017] Furthermore, the positive sequence impedance of the grid-connected inverter The calculation formula is: ,in, This is the port output impedance transfer function for a grid-connected inverter.

[0018] Furthermore, the total equivalent output impedance The calculation formula is: .

[0019] Furthermore, the formula for calculating the system passive margin at the current k is as follows:

[0020] in, To perform the minimum value operation, This is for the operation of taking the real part.

[0021] Furthermore, the analysis frequency band is determined based on the oscillation frequency band of interest to the site and the control bandwidth of grid-connected and grid-connected inverters; in this embodiment of the invention, it is preferably 1Hz to 100Hz.

[0022] The present invention also provides a new energy grid-connected system, including n inverters connected in parallel, where n is a positive integer and n>1. The new energy grid-connected system uses the above-mentioned grid-connected hybrid power station capacity allocation method to calculate the minimum capacity ratio of the grid-connected inverters.

[0023] Furthermore, each inverter includes a DC source, a three-phase inverter bridge, and a three-phase filter connected in series. The three-phase filter includes a filter inductor, a filter capacitor, and a passive damping resistor.

[0024] The present invention also provides an electronic device, including a memory and a processor, wherein the memory is used to store a program that supports the processor in executing the above-described method for capacity allocation of hybrid power stations connected to the grid, and the processor is configured to execute the program stored in the memory.

[0025] The present invention also provides a storage medium storing a computer program, which, when executed by a processor, performs the steps of the above-described method for capacity allocation of hybrid power stations connected to a grid.

[0026] The beneficial effects of this invention are as follows: This invention establishes a quantitative capacity determination link based on "GFL / GFM positive sequence port impedance - capacity ratio weighted parallel aggregation - minimum impedance real part passive margin of the target analysis frequency band - minimum feasible GFM capacity ratio". Compared with capacity estimation methods that only use scalar grid strength indicators such as SCR / gSCR, the capacity criterion of this invention is directly composed of two types of inverter port impedances, which can retain the frequency-related dynamic characteristics formed by control links such as PLL, current loop, voltage loop, and droop loop in capacity calculation. This invention defines the minimum real part of the total equivalent output impedance of the station within the target analysis frequency band as the passive margin PM(k), and uses PM(k)≥0 as the passive stability constraint of the target frequency band. Because the minimum real part corresponding to the most unfavorable frequency point is used as a scalar index, the capacity allocation result can correspond to the specific impedance-weak frequency point, avoiding the situation where it is difficult to distinguish the frequency characteristics of different controllers based solely on a single grid strength value. After obtaining the port impedances of GFL and GFM, this invention only requires frequency domain aggregation and frequency sweep calculation of the capacity proportion. It does not require rebuilding a complete electromagnetic transient model for each candidate capacity value, nor does it require repeatedly constructing high-order state-space matrices and performing eigenvalue, modal, or semidefinite programming optimization. Therefore, when control parameters, grid impedance, or equipment rated parameters change, the capacity boundary can be recalculated by updating the corresponding port impedances, facilitating site selection and parameter sensitivity analysis. In this embodiment of the invention, the power station includes 100 inverters, each with a rated power of 20kW, for a total rated capacity of 2.00MW. The capacity ergodic step size is Δk=0.02. Frequency domain calculation yields kmin=0.16, meaning that the minimum feasible grid capacity satisfying PM(k)≥0 under this discrete ergodic resolution is 0.32MW. For the equal-capacity units in this embodiment, 16 20kW inverters are used with grid-type control. As a control below this boundary, k=0.12 corresponds to 0.24MW, i.e., 12 20kW grid-type inverters. The time-domain simulation shows continuously increasing oscillations and unstable operation. When k=0.16, the system output waveform remains stable, indicating that the frequency domain capacity boundary given by this invention is consistent with the set time-domain control result. As can be seen from the above embodiments, increasing the verified instability ratio k=0.12 to the minimum feasible ratio k=0.16 calculated by this invention only requires an increase of 0.04 in the grid capacity ratio, i.e., an increase of 80kW in grid capacity, corresponding to four 20kW units of equal capacity. Compared to the scheme of using grid-type control for all 2.00MW power plants, the 0.32MW grid capacity calculated in this embodiment reduces the grid-type installation or retrofit capacity by 1.68MW, i.e., a reduction of 84%. This ratio is only used to illustrate the reduction in grid capacity and is not equivalent to a reduction in construction costs by the same proportion, but it can directly support the engineering effect of "avoiding excessive grid configuration". This invention outputs the minimum feasible capacity percentage that satisfies the passive stability constraint under a given traversal range and traversal step size, rather than an arbitrary stable percentage. In engineering applications, Δk can be set according to the rated capacity of a single unit, the granularity of the modification, or the required calculation accuracy. If necessary, the capacity boundary can be further refined by reducing Δk. Therefore, this invention can be used for GFL / GFM capacity planning of newly built renewable energy power plants, as well as for capacity scheme selection for the grid-based transformation of existing power plants, and can serve as a quantitative initial boundary for subsequent time-domain simulations or hardware experiments. Attached Figure Description

[0027] Figure 1 This is a topology diagram of the new energy grid-connected system according to Embodiment 1 of the present invention; Figure 2 This is a flowchart of the capacity allocation method for hybrid power stations based on frequency domain analytical calculation according to Embodiment 1 of the present invention; Figure 3 This is a graph showing the calculation results of the passive margin of the capacity allocation method for hybrid power stations based on frequency domain analytical calculation according to Embodiment 1 of the present invention. Figure 4 This is the waveform of the hybrid system output when k=0.12; Figure 5The minimum capacity ratio k of the grid-connected inverters is calculated using the frequency domain analytical calculation-based capacity allocation method for grid-connected hybrid power stations according to Embodiment 1 of this invention. min The waveform of the system output when =0.16. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] The technical solution of the present invention will be further described below with reference to the accompanying drawings and specific embodiments: Example 1 like Figure 1 The diagram shown illustrates the topology of the new energy grid-connected system in this embodiment. The system consists of n inverters connected in parallel, where n is a positive integer and n>1. Each inverter includes a DC source, a three-phase inverter bridge, and a three-phase filter connected in series. The three-phase filter includes a filter inductor, a filter capacitor, and a passive damping resistor. Figure 1 In the middle, V dc L is the DC side voltage. f C is the inductance value of the filter inductor. f r is the capacitance value of the filter capacitor. f C is the resistance value of the equivalent resistance of the inductance on the bridge arm side. dc e is the capacitance value of the DC capacitor. gabc For a three-phase power grid, L g This represents the inductance value of the power grid line.

[0030] like Figure 2 As shown, the capacity allocation method for hybrid power stations based on frequency domain analytical calculation in this embodiment includes the following steps: Step 1: Input the main system parameters of the grid inverter: main circuit parameters, control parameters, grid parameters, and analyze the frequency band.

[0031] In this embodiment, the main circuit parameters are: n=100, meaning it includes 100 inverters. dc =770V, L f =0.9mH, C f =11.6μF, passive damping resistor r f =2.18Ω; the inverter's rated output line voltage is 380V / 50Hz, and the rated power of a single inverter is 20kW; the grid parameters are: L g=0.1925mH, the analysis frequency band is from 1Hz to 100Hz.

[0032] Step 1.1: The control steps and parameters for the following network pattern mode are as follows: Step 1.1.1: Sample and output the grid-connected current i ga i gb i gc Sample the voltage u at the PCC point pcca ,u pccb ,u pccc .

[0033] Step 1.1.2: The PCC point voltage u obtained in step 1.1.1 is... pcca ,u pccb ,u pccc The dq-axis component u of the PCC point voltage is obtained by transforming from a three-phase stationary coordinate system to a two-phase rotating coordinate system. pccd ,u pccq ; Set the voltage u at point PCC pcca ,u pccb ,u pccc The phase angle θ of the voltage at point PCC is obtained by phase locking through a phase-locked loop (PLL); the formula for calculating the phase angle θ of the voltage at point PCC is:

[0034] Where ω0 is the rated angular frequency of the voltage at point PCC, K p_PLL K is the proportional control coefficient of the phase-locked loop PI controller. i_PLL ω0 represents the integral control coefficient of the phase-locked loop PI controller, and s represents the Laplace operator. In the specific implementation, ω0 = 314 rad / s, K0 p_PLL =0.28, K i_PLL =12.

[0035] PCC point voltage u pcca ,u pccb ,u pccc The transformation equation from a three-phase stationary coordinate system to a two-phase rotating coordinate system is:

[0036] Step 1.1.3: Based on the phase angle θ of the PCC point voltage obtained in Step 1.1.2, the output grid-connected current i sampled in Step 1.1.1 is... ga i gb i gc Transformed into the output grid-connected current dq component i in a two-phase rotating coordinate system gd i gq .

[0037] Output grid current i ga igb i gc The transformation equation from a three-phase stationary coordinate system to a two-phase rotating coordinate system is:

[0038] Step 1.1.4, set the dq axis output grid-connected current command signal i gdref i gqref And based on the output grid-connected current dq component i obtained in step 1.1.3 gd i gq The dq-axis control signal u is obtained through the closed-loop control equation of the power grid current. d ,u q The closed-loop control equation for the grid current is:

[0039] Among them, K p K represents the proportional control coefficient of the PI regulator in the closed-loop control equation of the power grid current. i K represents the integral control coefficient of the PI regulator in the closed-loop control equation of the power grid current. In specific implementation, K... p =4,K i =10.

[0040] Step 1.1.5: Based on the PCC point voltage phase angle θ obtained in Step 1.1.2, adjust the dq axis control signal u obtained in Step 1.1.4. d ,u q After transformation from a two-phase rotating coordinate system to a three-phase stationary coordinate system, the signal is converted into a control signal component u in the three-phase stationary coordinate system. a ,u b ,u c .

[0041] dq axis control signal u d ,u q The transformation equation from a two-phase rotating coordinate system to a three-phase stationary coordinate system is:

[0042] Step 1.1.6, convert the control signal components u in the three-phase stationary coordinate system obtained in step 1.1.5 into... a ,u b ,u c The voltage u at point PCC obtained in step 1.1.1 is compared with the voltage u at point PCC obtained in step 1.1.1. pcca ,u pccb ,u pccc Adding them together, we obtain the three-phase grid-connected inverter bridge arm voltage control signals, which are u a +u pcca ,u b +u pccb ,uc +u pccc The switching signals for the power devices of the grid-connected inverter are then generated through SPWM modulation, and the power devices of the three-phase inverter bridge are controlled by the drive circuit to turn on and off.

[0043] Step 1.2, the control steps and control parameters for the network-type mode are as follows: Step 1.2.1, sample and output the grid-connected current i ga i gb i gc Sample the voltage u at the PCC point pcca ,u pccb ,u pccc .

[0044] Step 1.2.2, the output grid-connected current i obtained from step 1.2.1 is... ga i gb i gc The αβ axis components of the output grid-connected current are obtained by transforming from a three-phase stationary coordinate system to a two-phase stationary coordinate system. gα i gβ The PCC point voltage u sampled in step 1.2.1 pcca ,u pccb ,u pccc The αβ axis components u of the PCC point voltage are obtained by transforming from a three-phase stationary coordinate system to a two-phase stationary coordinate system. pccα ,u pccβ .

[0045] Output grid current i ga i gb i gc The transformation equation from a three-phase stationary coordinate system to a two-phase stationary coordinate system is:

[0046] PCC point voltage u pcca ,u pccb ,u pccc The transformation equation from a three-phase stationary coordinate system to a two-phase stationary coordinate system is:

[0047] Step 1.2.3, based on the output grid-connected current αβ-axis component i obtained in step 1.2.2 gα i gβ And the αβ axis component u of the PCC point voltage pccα ,u pccβ First, the average active power is obtained through the average active power calculation equation. Then, the average reactive power is obtained through the average reactive power calculation equation. The calculation equations are as follows:

[0048]

[0049] Where τ is the time constant of the first-order low-pass filter, and s is the Laplace operator. In the specific implementation, τ = 0.00318s.

[0050] Step 1.2.4, based on the average active power obtained in step 1.2.3 The output angular frequency ω of the grid-connected inverter is obtained through the active power-frequency droop control equation. And the output phase angle θ0 of the grid-connected inverter is calculated, θ0 = ω / s, where P n To provide an active power command to the grid-connected inverter, ω n Given the active power command P n The corresponding rated angular frequency, D p This is the active power droop coefficient. In specific implementation, ω n =314 rad / s, P n =20kW, D p =0.0001.

[0051] Step 1.2.5, based on the PCC point voltage u sampled in step 1.2.1 pcca ,u pccb ,u pccc The output phase angle θ0 of the grid-connected inverter obtained in step 1.2.4 is transformed from a three-phase stationary coordinate system to a two-phase rotating coordinate system to obtain the dq-axis component u of the PCC point voltage. pccd ,u pccq .

[0052] PCC point voltage u pcca ,u pccb ,u pccc The transformation equation from a three-phase stationary coordinate system to a two-phase rotating coordinate system is:

[0053] Step 1.2.6, based on the output grid-connected current i sampled in step 1.2.1 ga i gb i gc The output phase angle θ0 of the grid-connected inverter obtained in step 1.2.4 is transformed from a three-phase stationary coordinate system to a two-phase rotating coordinate system to obtain the output grid-connected current dq component i. gd i gq .

[0054] Output grid current i ga i gb i gcThe transformation equation from a three-phase stationary coordinate system to a two-phase rotating coordinate system is:

[0055] Step 1.2.7, based on the average reactive power output of the grid-connected inverter obtained in Step 1.2.3. The reference value u of the dq component of the PCC point voltage of the grid-connected inverter is obtained through the reactive power-amplitude droop control equation. pccdref ,u pccqref The reactive power-amplitude droop control equation is:

[0056]

[0057] Among them, U n For grid-connected inverters, when giving reactive power command Q n The corresponding rated output voltage, D q This is the reactive power droop factor. In specific implementation, U n =220V, Q n =0, D q =0.0001.

[0058] Step 1.2.8, based on the PCC point voltage dq-axis component u obtained in step 1.2.5 pccd ,u pccq The reference value u of the dq component of the PCC point voltage obtained in step 1.2.7 pccdref ,u pccqref The grid-connected current command signal i for the dq axis output is obtained through the voltage loop control equation. gdref i gqref The voltage loop control equation is as follows:

[0059] Among them, K p1 K represents the proportional control coefficient of the PI regulator in the voltage loop control equation. i1 K represents the integral control coefficient of the PI regulator in the voltage loop control equation. In specific implementation, K... p1 =0.05, K i1 =120.

[0060] Step 1.2.9: Based on the dq axis output grid-connected current command signal i obtained in step 1.2.8. gdref i gqref And based on the output grid-connected current dq component i obtained in step 1.2.6 gd i gq The dq-axis control signal u is obtained through the current loop control equation. d ,uq The current loop control equation is:

[0061] Among them, K p2 K represents the proportional control coefficient of the PI regulator in the current loop control equation. i2 K represents the integral control coefficient of the PI controller in the current loop control equation. In a specific example, K... p2 =4,K i2 =10.

[0062] Step 1.2.10, convert the dq axis control signal u obtained in step 1.2.9 into... d ,u q The control signal component u is transformed from a two-phase rotating coordinate system to a three-phase stationary coordinate system. a ,u b ,u c .

[0063] dq axis control signal u d ,u q The transformation equation from a two-phase rotating coordinate system to a three-phase stationary coordinate system is:

[0064] Step 1.2.11, convert the components u in the three-phase stationary coordinate system obtained in step 1.2.10. a ,u b ,u c Compare the PCC point voltage u obtained in step 1.2.1 with the voltage u of the PCC point obtained in step 1.2.1. pcca ,u pccb ,u pccc Adding them together, we obtain the three-phase grid-connected inverter bridge arm voltage control signal u. a +u pcca ,u b +u pccb ,u c +u pccc The switching signals for the power devices of the grid-connected inverter are then generated through SPWM modulation, and the switching signals are controlled by the drive circuit to turn on and off the power devices of the three-phase inverter bridge.

[0065] Step 2: Establish positive sequence impedance models for grid-connected and grid-connected inverters. and .

[0066] The positive sequence impedance model of the grid-connected inverter The calculation formula is as follows:

[0067] The positive sequence impedance of the grid-type inverter The calculation formula is as follows:

[0068] in, ; ; ; ; ; ; ; ; ; ; ; .

[0069] The meanings of each parameter are explained below: Let be the transfer function of the filter capacitor and its damping resistor. This represents the resistance value of the equivalent resistance of the inductance on the bridge arm side. This is the capacitance value of the filter capacitor; To determine the port output impedance transfer function of a grid-type inverter. This is the inductance value of the filter inductor. This is the transfer function of the PI regulator for closed-loop control of the power grid current. This is the decoupling coefficient of the current loop. This is the small-signal transfer function of the phase-locked loop. For grid voltage feedforward coefficient, This represents the proportional control coefficient of the PI regulator in the closed-loop control equation of the power grid current. These are the integral control coefficients of the PI regulator in the closed-loop control equation of the power grid current. This refers to the proportional control coefficient of the phase-locked loop PI controller. This is the integral control coefficient of the phase-locked loop PI controller; The port output impedance transfer function of a grid-connected inverter. The numerator coefficient of the port output impedance transfer function for a grid-connected inverter is given. The denominator coefficients of the port output impedance transfer function for a grid-connected inverter. This is the small-signal transfer function for the active droop loop. For the small-signal transfer function of the reactive power droop loop. Let be the transfer function of the PI regulator in the voltage loop control equation. Let be the transfer function of the PI regulator in the current loop control equation. This represents the proportional control coefficient of the PI regulator in the voltage loop control equation. These are the integral control coefficients of the PI regulator in the voltage loop control equation. This represents the proportional control coefficient of the PI regulator in the current loop control equation. These are the integral control coefficients of the PI controller in the current loop control equation. The time constant of the first-order low-pass filter. This is the active power droop coefficient. This is the reactive power droop factor. For the Laplace operator, It is the imaginary unit.

[0070] Step 3: Define the rated capacity ratio of grid-connected inverters as k, k∈[0,1], and the rated capacity ratio of root-connected inverters as (1-k) under a unified rated capacity benchmark; determine the traversal range of k [k1,k2] and set the traversal step size Δk, where k1 is the lower limit of the traversal range and k2 is the upper limit of the traversal range. Preferably, in this embodiment, Δk is 0.02 and the traversal range is [0,1]. Since the rated capacity of each of the 100 inverters in this embodiment is 20kW, the capacity ratio can directly correspond to the number of units with the same capacity.

[0071] Step 4: Under a unified rated capacity benchmark, perform capacity-weighted parallel equivalent calculations on the two types of positive-sequence port admittances according to the capacity ratio k of the network configuration and the capacity ratio (1-k) of the follow-up network configuration, and establish the total equivalent output impedance of the station. Its expression is: .

[0072] Step 5: Iterate through each capacity percentage k within the range [k1, k2].

[0073] Step 5.1: For the current k, calculate its total equivalent output impedance within the analysis frequency band according to the formula in Step 4. , where j is the imaginary unit and ω is the angular frequency corresponding to the analysis frequency band; in this embodiment, the range of ω is [2π, 200π].

[0074] Step 5.2: Define the minimum value of the real part of the total equivalent output impedance within the analysis frequency band as the system passive margin at the current k. ,in, To perform the minimum value operation, This is for the operation of taking the real part.

[0075] Step 5.3, Margin Judgment: Based on the sufficient passive condition within the analyzed frequency band, if Record the current k and exit the loop; if PM(k) < 0 and k + Δk ≤ k2, then let k = k + Δk and return to step 5.1 to continue traversing; if PM(k) < 0 and k + Δk > k2, then output the capacity percentage that does not meet the passive margin requirement within the current traversal range and end.

[0076] Step 6: Output the minimum k that satisfies the non-negativity condition of passive margin under the given traversal range and traversal step size, i.e., the minimum rated capacity ratio k of the minimum grid-type inverter (GFM). min In this embodiment, the passive margin calculation result is as follows: Figure 3 As shown, k is obtained at a discrete ergodic resolution of Δk=0.02. min =0.16. Since the total rated capacity of the power station is 100×20kW=2.00MW, the corresponding minimum feasible grid capacity is 0.16×2.00MW=0.32MW, which corresponds to 16 20kW inverters of equal capacity using grid-type control.

[0077] Simulation verification To verify the effectiveness of the capacity boundary given by the method of this invention, the frequency domain calculation results were compared with the time domain simulation results in MATLAB / Simulink. The results are as follows: Figure 4 and Figure 5 As shown. Figure 4 This corresponds to k=0.12, which means a grid capacity of 0.24MW, corresponding to 12 grid-connected inverters of equal capacity (20kW each). This proportion is lower than the k calculated in the frequency domain. min =0.16, the amplitude of the system current oscillation continued to increase in the simulation, and it could not maintain stable operation. Figure 5 Corresponding to k=k min =0.16, meaning a grid capacity of 0.32MW, corresponding to 16 20kW grid-type inverters, allows the system output current to remain stable. Therefore, in this embodiment, given the parameters and the analysis frequency band from 1Hz to 100Hz, the discrete minimum capacity boundary given by the frequency domain passive margin is consistent with the time domain comparison results for k=0.12 and k=0.16. Compared to k=0.12, only an increase of 80kW, or 4 20kW grid-type inverters, is needed to cross the discrete stability boundary of this embodiment.

[0078] Example 2 This embodiment provides an electronic device, including a memory and a processor.

[0079] The memory is used to store a computer program that supports the processor in executing the capacity allocation method for hybrid power stations as described in Embodiment 1. The memory can be a high-speed random access memory or a non-volatile memory, such as a disk storage device, flash memory device, or other solid-state storage device.

[0080] The processor is configured to execute a program stored in the memory. The processor may be a general-purpose central processing unit, a dedicated processor, a microprocessor, or a digital signal processor.

[0081] The electronic device may also include a communication interface for exchanging data with other computing nodes or storage devices. The communication interface may be a wired interface (such as an Ethernet interface) or a wireless interface.

[0082] The electronic device may also include input / output interfaces for connecting peripheral devices such as displays, keyboards, and mice, so that users can view the computing status and input control commands.

[0083] Example 3 This embodiment provides a storage medium on which a computer program is stored.

[0084] The storage medium can be any medium capable of storing program code, including but not limited to: USB flash drive, portable hard drive, read-only memory, random access memory, magnetic disk, optical disk, flash memory card, etc.

[0085] The computer program, when run by the processor, executes the steps of the capacity allocation method for hybrid power stations as described in Embodiment 1.

[0086] The storage medium can be located on a single computing device or distributed across multiple computing devices, such as in a distributed storage system. The program can be loaded onto a single processor for execution or loaded onto multiple processors for parallel execution.

[0087] The above 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.

Claims

1. A method for capacity allocation of hybrid power stations connected to a grid, characterized in that, Includes the following steps: S1. Input the system parameters of the grid inverter, including: main circuit parameters, control parameters, grid parameters and analysis frequency band; S2. Establish the positive sequence impedance models for grid-connected and mesh-type inverters. GFL (s) and Z GFM (s); S3. Under the unified rated capacity benchmark, define the rated capacity ratio of grid-type inverters as k, k∈[0,1], and determine the rated capacity ratio of grid-connected inverters as (1-k); determine the traversal range of k [k1,k2] and set the traversal step size △k, where k1 is the lower limit of the traversal range and k2 is the upper limit of the traversal range. S4. Under a unified rated capacity benchmark, the capacity weighted parallel equivalent of the two types of positive sequence port admittances is performed according to the capacity ratio k of the network type and the capacity ratio (1-k) of the follow-up network type, and the total equivalent output impedance of the station is established. ; S5. Iterate through each capacity percentage k within the range [k1, k2]; S5.1 For the current k, calculate its total equivalent output impedance within the analysis frequency band. Where j is the imaginary unit and ω is the corresponding angular frequency within the analysis band; S5.2, Define the minimum value of the real part of the total equivalent output impedance within the analysis frequency band as the passive margin of the system at the current k. ; S5.3 Margin Judgment: Based on the sufficient condition of passivity, within the analysis frequency band, if PM(k)≥0, record the current k and exit the loop; if PM(k)<0 and k+△k≤k2, let k=k+△k and return to step S5.1 to continue traversing; if PM(k)<0 and k+△k>k2, output the capacity percentage that does not meet the passive margin requirement within the current traversal range and end. S6. Output the smallest k that satisfies PM(k)≥0 under a given traversal range and traversal step size, as the minimum grid-type inverter rated capacity percentage k that satisfies the passive stability constraint of the analysis frequency band. min .

2. The capacity allocation method for hybrid power stations according to claim 1, characterized in that, The positive sequence impedance model of the grid-connected inverter The calculation formula is: ,in, Let be the transfer function of the filter capacitor and its damping resistor. This is the port output impedance transfer function for a grid-connected inverter.

3. The capacity allocation method for hybrid power stations according to claim 2, characterized in that, The positive sequence impedance of the grid-type inverter The calculation formula is: ,in, This is the port output impedance transfer function for a grid-connected inverter.

4. The capacity allocation method for hybrid power stations according to claim 3, characterized in that, The total equivalent output impedance The calculation formula is: .

5. The capacity allocation method for hybrid power stations according to claim 1, characterized in that, The formula for calculating the passive margin of the system at the current k is as follows: in, To perform the minimum value operation, This is for the operation of taking the real part.

6. The capacity allocation method for hybrid power stations according to claim 1, characterized in that, The analysis frequency band is from 1Hz to 100Hz.

7. A new energy grid-connected system, comprising n inverters connected in parallel, where n is a positive integer and n>1, characterized in that, The new energy grid-connected system uses the capacity allocation method of any one of claims 1 to 6 to calculate the minimum capacity ratio of the grid-connected inverter.

8. The new energy grid connection system according to claim 7, characterized in that, Each inverter includes a DC source, a three-phase inverter bridge, and a three-phase filter connected in series. The three-phase filter includes a filter inductor, a filter capacitor, and a passive damping resistor.

9. An electronic device, comprising a memory and a processor, characterized in that, The memory is used to store a program that supports the processor in executing the capacity allocation method for hybrid power stations according to any one of claims 1 to 6, and the processor is configured to execute the program stored in the memory.

10. A storage medium storing a computer program, characterized in that, When a computer program is run by a processor, it executes the steps of the capacity allocation method for hybrid power stations as described in any one of claims 1 to 6.

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