Impedance prediction method and device for a photovoltaic system of unknown structure

Abstract

The application belongs to the technical field of photovoltaic power generation, and provides an impedance prediction method and device for a photovoltaic system with unknown structure, the impedance prediction method for the photovoltaic system with unknown structure comprising: injecting a disturbance signal at a predetermined stable working point of the photovoltaic system with unknown structure to generate a frequency impedance curve of the stable working point; wherein the frequency of the disturbance signal is determined by the power frequency of the photovoltaic system with unknown structure; converting the frequency impedance curve into an equivalent complex function; wherein the variable of the equivalent complex function is the active power and the reactive power of the photovoltaic system with unknown structure; obtaining the expansion formula of the Taylor series of the equivalent complex function, and predicting the impedance of the photovoltaic system with unknown structure through the expansion formula. The application is based on limited known impedance data of working conditions, and can quickly and accurately predict the impedance model of the photovoltaic system with unknown structure under any other operating condition, thereby avoiding repeated impedance scanning simulation for each working condition.

Description

Technical Field

[0001] This application belongs to the field of photovoltaic power generation technology, particularly the field of photovoltaic power system stability analysis technology, specifically an impedance prediction method and device for a photovoltaic system with unknown structure. Background Technology

[0002] For impedance prediction methods of photovoltaic systems with unknown structures, existing technologies generally involve impedance scanning of the photovoltaic unit under specific operating conditions to obtain the impedance frequency response curve under those conditions. This method relies on simulation techniques, obtaining impedance curve data at different operating points (such as different active power P and reactive power Q) by changing the operating conditions.

[0003] The aforementioned existing technical solutions have significant drawbacks: First, this method is essentially a "one-point-one-measurement" approach, meaning that each impedance scan can only obtain the impedance characteristics under a single specific operating condition. To obtain impedance models under a large number of different operating conditions, frequent and tedious simulation calculations are required, resulting in low efficiency and difficulty in achieving rapid modeling. Second, this method lacks a theoretical model for deriving the impedance of unknown operating conditions from known operating condition impedances, and cannot establish a mathematical relationship between operating conditions and impedance models. Consequently, its predictive ability is insufficient, and its accuracy and universality are limited. Summary of the Invention

[0004] The present invention provides an impedance prediction method for photovoltaic systems with unknown structures, aiming to solve at least some of the aforementioned technical problems.

[0005] Another object of the present invention is to provide an impedance prediction device for a photovoltaic system with an unknown structure. A further object of the present invention is to provide an electronic device comprising a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps of the impedance prediction method for a photovoltaic system with an unknown structure described above. A further object of the present invention is to provide a readable medium storing a computer program thereon, the computer program being executed by a processor to implement the steps of the impedance prediction method for a photovoltaic system with an unknown structure described above.

[0006] In a first aspect, the present invention provides an impedance prediction method for a photovoltaic system with an unknown structure, the method comprising: A perturbation signal is injected into a predetermined stable operating point of a photovoltaic system with an unknown structure to generate a frequency impedance curve of the stable operating point; wherein the frequency of the perturbation signal is determined by the power frequency of the photovoltaic system with an unknown structure. The frequency impedance curve is converted into an equivalent complex function; wherein the variables of the equivalent complex function are the active power and reactive power of the photovoltaic system with unknown structure. The Taylor series expansion of the equivalent complex function is obtained, and the impedance of the photovoltaic system with unknown structure is predicted using the expansion.

[0007] In some embodiments of this application, the disturbance signal is a voltage sequence with a preset amplitude; generating the frequency impedance curve of the stable operating point includes: Measure the current change in a photovoltaic system with an unknown structure caused by the injection of the disturbance signal; The frequency impedance curve is generated based on the voltage sequence and the current change.

[0008] In some embodiments of this application, converting the frequency impedance curve into an equivalent complex function includes: The real angular frequency and complex frequency of the equivalent complex function are determined based on the frequency impedance curve. A transfer function is generated based on the complex frequency and the real angular frequency; The transfer function is subjected to a Laplace transform to generate the equivalent complex function.

[0009] In some embodiments of this application, the complex frequency is used to characterize the amplitude change of the disturbance signal; determining the real angular frequency and complex frequency of the equivalent complex function based on the frequency impedance curve includes: Determine the poles, inflection points, and slope of the frequency impedance curve; The real angular frequency and the complex frequency are determined based on the frequency impedance curves corresponding to the poles and inflection points, as well as the slope.

[0010] In some embodiments of this application, the step of determining the stable operating point includes: Adjust the operating point of the photovoltaic system with unknown structure to determine the maximum power point of the photovoltaic system with unknown structure; Measure the DC-side power at the maximum power point to determine the active power; The reactive power is determined based on the voltage deviation at the grid connection point of the photovoltaic system with unknown structure. The stable operating point is determined based on the active power and the reactive power.

[0011] In some embodiments of this application, the equivalent complex function is:

[0012] In the formula, The equivalent complex function is... , , , , , , , , , , , , , , For the grid-side filter inductor, R s Here is the grid-side filter resistor, s is the frequency domain, and V is the voltage. dc For DC voltage, N s Let N be the equivalent transfer function of the outer loop of the grid-side converter. r Let be the equivalent transfer function of the inner loop of the grid-side converter. V is the proportional parameter of the phase-locked loop. 1为 Grid-side system voltage, 50Hz The voltage of the photovoltaic electric field. For the boost circuit inductor, This refers to the duty cycle of the boost circuit switch.

[0013] Secondly, the present invention provides an impedance prediction device for a photovoltaic system with an unknown structure, the device comprising: A frequency impedance curve generation module is used to inject a disturbance signal into a predetermined stable operating point of a photovoltaic system with an unknown structure, and generate a frequency impedance curve of the stable operating point; wherein, the frequency of the disturbance signal is determined by the power frequency of the photovoltaic system with an unknown structure. A frequency impedance curve conversion module is used to convert the frequency impedance curve into an equivalent complex function; wherein the variables of the equivalent complex function are the active power and reactive power of the photovoltaic system with unknown structure. The Taylor series expansion module is used to obtain the Taylor series expansion of the equivalent complex function and predict the impedance of the photovoltaic system with unknown structure using the expansion.

[0014] In some embodiments of this application, the disturbance signal is a voltage sequence with a preset amplitude; the frequency impedance curve generated by the frequency impedance curve generation module for the stable operating point includes: A current change measurement unit is used to measure the current change of a photovoltaic system with an unknown structure caused by the injection of the disturbance signal; A frequency impedance curve generation unit is used to generate the frequency impedance curve based on the voltage sequence and the current change.

[0015] In some embodiments of this application, the frequency impedance curve conversion module includes: The complex frequency determination unit is used to determine the real angular frequency and complex frequency of the equivalent complex variable function based on the frequency impedance curve. A transfer function generation unit is used to generate a transfer function based on the complex frequency and the real angular frequency; An equivalent complex function generation unit is used to perform a Laplace transform on the transfer function to generate the equivalent complex function.

[0016] In some embodiments of this application, the complex frequency is used to characterize the amplitude change of the disturbance signal; the complex frequency determination unit includes: A frequency impedance curve characteristic determination unit is used to determine the poles, inflection points, and slope of the frequency impedance curve. The complex frequency determination subunit is used to determine the real angular frequency and the complex frequency based on the frequency impedance curves corresponding to the poles and the inflection points, as well as the slope.

[0017] In some embodiments of this application, an impedance prediction device for a photovoltaic system with an unknown structure further includes: Stable operating point determination module, used to determine the stable operating point; stable operating point determination module includes: A maximum power point determination unit is used to adjust the operating point of the photovoltaic system with unknown structure and determine the maximum power point of the photovoltaic system with unknown structure. An active power determination unit is used to measure the DC-side power at the maximum power point and determine the active power. A reactive power determination unit is used to determine the reactive power based on the voltage deviation at the grid connection point of the photovoltaic system with unknown structure. A stable operating point unit is used to determine the stable operating point based on the active power and the reactive power.

[0018] Thirdly, the present invention provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of an impedance prediction method for a photovoltaic system with an unknown structure.

[0019] Fourthly, the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of an impedance prediction method for a photovoltaic system with an unknown structure.

[0020] Fifthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of an impedance prediction method for a photovoltaic system with an unknown structure.

[0021] As described above, embodiments of the present invention provide an impedance prediction method and apparatus for a photovoltaic system with an unknown structure. The impedance prediction method for a photovoltaic system with an unknown structure includes: first, injecting a disturbance signal at a predetermined stable operating point of the photovoltaic system with an unknown structure to generate a frequency impedance curve at the stable operating point; wherein the frequency of the disturbance signal is determined by the power frequency of the photovoltaic system with an unknown structure; next, converting the frequency impedance curve into an equivalent complex function; wherein the variables of the equivalent complex function are the predetermined active power and reactive power of the photovoltaic system with an unknown structure; finally, obtaining the Taylor series expansion of the equivalent complex function, and predicting the impedance of the photovoltaic system with an unknown structure through the expansion.

[0022] In summary, this invention, based on limited known impedance data, rapidly and accurately pre-structures impedance models of unknown photovoltaic systems under any other operating conditions (characterized by active and reactive power), thereby avoiding repeated impedance scanning simulations for each operating condition. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 A schematic flowchart of an impedance prediction method for a photovoltaic system with an unknown structure, as described in an embodiment of the present invention; Figure 2 This is a flowchart illustrating step 100 in an embodiment of the present invention; Figure 3 This is a flowchart illustrating step 200 in an embodiment of the present invention; Figure 4 This is a flowchart illustrating step 201 in an embodiment of the present invention; Figure 5 Another flowchart illustrating an impedance prediction method for a photovoltaic system with an unknown structure, as described in an embodiment of the present invention. Figure 6 This is a flowchart illustrating step 400 in an embodiment of the present invention; Figure 7 This is a flowchart illustrating an impedance prediction method for a photovoltaic system with an unknown structure, as described in a specific embodiment of the present invention. Figure 8 This is a block diagram of an impedance prediction device for a photovoltaic system with an unknown structure, as described in an embodiment of the present invention. Figure 9This is a block diagram of the frequency impedance curve generation module 10 in an embodiment of the present invention; Figure 10 This is a block diagram of the frequency impedance curve conversion module 20 in an embodiment of the present invention; Figure 11 This is a block diagram of the complex frequency determination unit 20a in an embodiment of the present invention; Figure 12 This is another block diagram of an impedance prediction device for a photovoltaic system with an unknown structure, as described in an embodiment of the present invention. Figure 13 A block diagram of the stable operating point determination module 40 in an embodiment of the present invention; Figure 14 This is a schematic diagram of the structure of an electronic device in an embodiment of the present invention. Detailed Implementation

[0025] 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 with reference to the accompanying drawings. 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.

[0026] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0027] It should be noted that the terms "comprising" and "having," and any variations thereof, in the specification, claims, and accompanying drawings of this application are intended to cover a non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or apparatuses. Without conflict, the embodiments and features in the embodiments of this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0028] In power system modeling, if the system's internal parameters, structure, and control strategy are completely known, the system can be defined as a "white box" system. Conversely, if the system's internal parameters or structure are partially or completely unknown, the system is classified as a "black box" system. For photovoltaic power generation systems, when they are considered "black box" systems, the unknown internal controller parameters make it impossible to directly establish an accurate frequency domain impedance model. This poses a challenge to analyzing stability issues (such as subsynchronous oscillations) caused by grid connection of photovoltaic units. To address these issues and to resolve at least some of the technical problems in the background of this application, embodiments of the present invention provide a specific implementation of an impedance prediction method for photovoltaic systems with unknown structures, see [link to relevant documentation]. Figure 1 The method includes: Step 100: Inject a disturbance signal into a predetermined stable operating point of the photovoltaic system with unknown structure to generate a frequency impedance curve of the stable operating point; wherein, the frequency of the disturbance signal is determined by the power frequency of the photovoltaic system with unknown structure; Step 200: Convert the frequency impedance curve into an equivalent complex function; wherein the variables of the equivalent complex function are the active power and reactive power of the photovoltaic system with unknown structure. Step 300: Obtain the Taylor series expansion of the equivalent complex function, and predict the impedance of the photovoltaic system with unknown structure using the expansion.

[0029] As described above, embodiments of the present invention provide an impedance prediction method for a photovoltaic system with an unknown structure, comprising: first, injecting a disturbance signal at a predetermined stable operating point of the photovoltaic system with an unknown structure to generate a frequency impedance curve at the stable operating point; wherein the frequency of the disturbance signal is determined by the power frequency of the photovoltaic system with an unknown structure; next, converting the frequency impedance curve into an equivalent complex function; wherein the variables of the equivalent complex function are the predetermined active power and reactive power of the photovoltaic system with an unknown structure; finally, obtaining the Taylor series expansion of the equivalent complex function, and predicting the impedance of the photovoltaic system with an unknown structure through the expansion.

[0030] In summary, this invention, based on limited known impedance data, rapidly and accurately pre-structures impedance models of unknown photovoltaic systems under any other operating conditions (characterized by active and reactive power), thereby avoiding repeated impedance scanning simulations for each operating condition.

[0031] Regarding step 100, at a specific steady-state operating point of the photovoltaic system with unknown structure, a perturbation signal (voltage or current) with variable frequency and small amplitude is injected into the system, and the system response is measured to calculate the frequency domain impedance seen from the observation port at that operating point. For nonlinear time-varying systems like photovoltaic inverters, under small-signal perturbations, they can be linearized at a certain operating point and described using an equivalent impedance model. This impedance is a function of frequency.

[0032] For step 200, its essence is to measure or calculate the frequency response Z(jω) on the pure imaginary axis (jω axis), and then analytically extend it to the entire complex plane (s plane) to obtain an equivalent complex function Z(s).

[0033] The complex function Z(s) mentioned above has an independent variable s = σ + jω, which is a complex number, where σ is the real part (representing decay / growth) and jω is the imaginary part (representing oscillation).

[0034] For step 300, since the equivalent complex function in step 200 is complex and difficult to calculate, but the polynomial is easy to evaluate, differentiate, and integrate, we can find a polynomial by obtaining the Taylor series expansion of the equivalent complex function, such that its behavior is almost exactly the same as that of the complex function near a certain point.

[0035] In some embodiments of this application, the disturbance signal is a voltage sequence with a preset amplitude; see also Figure 2 Step 100, generating the frequency impedance curve of the stable operating point, includes: Step 101: Measure the current change of the photovoltaic system with unknown structure caused by the injection of the disturbance signal; At the grid connection point of the photovoltaic unit, a small-amplitude (preferably <5% of the fundamental amplitude) and variable-frequency disturbance signal is superimposed on the fundamental voltage using an impedance measuring device or a programmable grid simulator. The types of this disturbance signal include: A swept chirp signal is a sine wave whose frequency varies continuously from low to high (1Hz to 2kHz). Sweeped chirp signals are fast, and wideband data can be obtained with a single injection.

[0036] Multiple sine wave superposition: Multiple sine waves of different frequencies are injected simultaneously, each with a small amplitude and optimized phase to avoid excessively high peak values. Multiple sine wave superposition results in a high signal-to-noise ratio and short measurement time.

[0037] Pseudo-random binary sequence (PRBS): A wide-spectrum digital sequence that can effectively excite various frequencies of a system.

[0038] It should be noted that the amplitude of the aforementioned disturbance signal must be small enough to ensure that the system response is within the linear range (typically 1%-5% of the rated voltage / current), but not so small that it is drowned out by background noise.

[0039] Step 102: Generate the frequency impedance curve based on the voltage sequence and the current change.

[0040] Based on step 101, the system response (changes in voltage and current) is measured at the grid connection point to calculate the impedance curve over the entire frequency range, i.e., the frequency impedance curve.

[0041] In some embodiments of this application, see Figure 3 Step 200, converting the frequency impedance curve into an equivalent complex function, includes: Step 201: Determine the real angular frequency and complex frequency of the equivalent complex function based on the frequency impedance curve; Step 202: Generate a transfer function based on the complex frequency and the real angular frequency; Since the impedance of a real physical system corresponds to a causal and stable transfer function, the input-output relationship of a photovoltaic system with unknown structure can be described by the transfer function. The transfer function is essentially a function; specifically, it is a rational fractional function of the complex variable s (where both the numerator and denominator are polynomials of s).

[0042] Step 203: Perform a Laplace transform on the transfer function to generate the equivalent complex function.

[0043] The time-domain response of the system to arbitrary disturbances (such as voltage dips and current surges) is calculated using the inverse Laplace transform. Specifically, by writing the differential equations of the photovoltaic inverter circuit (inductor, capacitor) and the controller (PI, PLL), a Laplace transform is performed to obtain the algebraic equation in the s-domain, thereby deriving the equivalent complex function of the output impedance.

[0044] In some embodiments of this application, the complex frequency is used to characterize the amplitude variation of the disturbance signal; see also Figure 4 Step 201 includes: Step 2011: Determine the poles, inflection points, and slope of the frequency impedance curve; Step 2012: Determine the real angular frequency and the complex frequency based on the frequency impedance curves corresponding to the poles and inflection points, and the slope.

[0045] In steps 2011 and 2012, the characteristics of the frequency impedance curve (inflection point, resonance, slope) are identified, and the characteristic angular frequency and the complex frequency (pole) derived from it are given. Specifically: Amplitude-frequency curve slope change → first-order pole / zero point → complex frequency on the real axis; resonance peak / valley → second-order pole / zero point → complex conjugate pair; phase characteristic point → precise corner frequency → verifying pole / zero point location; combination characteristics → multi-timescale interaction → multi-pole / zero system (see Table 1).

[0046] Table 1

[0047] In some embodiments of this application, see Figure 5 An impedance prediction method for a photovoltaic system with unknown structure also includes: Step 400: Determine the stable operating point; then, see... Figure 6 Step 400 includes: Step 401: Adjust the operating point of the photovoltaic system with unknown structure to determine the maximum power point of the photovoltaic system with unknown structure; By continuously adjusting the operating point using the perturbation observation method or the incremental conductance method, the maximum power point under the current conditions can be found.

[0048] Step 402: Measure the DC-side power at the maximum power point to determine the active power; Specifically, step 402 can be performed using the following formula: Active power = DC side power × conversion efficiency - auxiliary system power consumption; Step 403: Determine the reactive power based on the voltage deviation at the grid connection point of the photovoltaic system with unknown structure; First, a voltage reference value is set, and the actual effective voltage value at the grid connection point (PCC) is continuously measured. Then, the voltage deviation in step 403 can be calculated in real time. Next, the reactive power is calculated based on the voltage deviation and the pre-established voltage-reactive power mapping function.

[0049] The voltage-reactive power mapping function described above is implemented using a droop characteristic curve with dead zone and saturation region. This function maps the voltage deviation to a setpoint for reactive power.

[0050] Step 404: Determine the stable operating point based on the active power and the reactive power.

[0051] The stable operating point refers to the state in which the inverter of a photovoltaic system can operate safely and for a long period of time at a certain moment. This state is completely defined by a set of electrical quantities.

[0052] Based on the active power (P) and reactive power (Q) mentioned above, the steady-state can be determined from two perspectives: one is the steady state as seen from the external power grid, and the other is the steady state of the inverter's internal control. The power balance of the external power grid (determines the amplitude and phase of voltage and current). The balance of the inverter's internal control loop (determines the internal variables that achieve this power output).

[0053] In some embodiments of this application, the equivalent complex function is:

[0054] In the formula, The equivalent complex function is... , , , , , , , , , , , , , , For the grid-side filter inductor, R s Here is the grid-side filter resistor, s is the frequency domain, and V is the voltage. dc For DC voltage, N s Let N be the equivalent transfer function of the outer loop of the grid-side converter. r Let be the equivalent transfer function of the inner loop of the grid-side converter. V is the proportional parameter of the phase-locked loop. 1为 Grid-side system voltage, 50Hz The voltage of the photovoltaic electric field. For boost circuit inductance, This refers to the duty cycle of the boost circuit switch.

[0055] Specifically, the frequency domain impedance of the photovoltaic unit under specific active power P and reactive power Q is obtained through impedance scanning, and it is equivalent to a complex function with P and Q as variables. The basic form of this function is:

[0056] in, , , , , , , , , , , , , , .

[0057] Then, After eliminating the imaginary number from the middle denominator, we can finally obtain:

[0058] in, , , , , , .

[0059] in, It is a stator inductor. It is a magnetizing inductor. For magnetic linkage, This is the sinusoidal angular frequency on the stator side. For the electric angle; The output phase angle of the phase-locked loop (PLL); the PLL transfer function is... ; , This is a reference value for the rotor-side current; , This is a reference value for the grid-side current; , For the rotor side Shaft current measurement value; , For the net side Shaft current measurement value; This refers to the rotor current. Voltage regulation for the rotor-side converter; Voltage modulation for grid-side converter This is the DC bus voltage; This refers to the three-phase output voltage of the stator. and This represents the d-axis and q-axis components of the three-phase output voltage of the machine-side converter in a synchronous rotating coordinate system. This is the three-phase current output by the machine-side converter; and These are the d-axis and q-axis components of the three-phase output current of the machine-side converter in the synchronous rotating coordinate system, respectively. and The three-phase regulation system of the machine-side converter is respectively d-axis and q-axis components in a synchronously rotating coordinate system; It is a PI controller for the current of the machine-side converter. This refers to the three-phase output current of the grid-side converter. and These represent the three-phase regulation of the grid-side converter in a synchronous rotating coordinate system. The d-axis and q-axis are divided; and These represent the d-axis and q-axis values ​​of the three-phase output current of the machine-side converter in a synchronous rotating coordinate system, respectively. It is a PI controller for the grid-side converter current.

[0060] As described above, embodiments of the present invention provide an impedance prediction method for a photovoltaic system with an unknown structure, comprising: first, injecting a disturbance signal at a predetermined stable operating point of the photovoltaic system with an unknown structure to generate a frequency impedance curve at the stable operating point; wherein the frequency of the disturbance signal is determined by the power frequency of the photovoltaic system with an unknown structure; next, converting the frequency impedance curve into an equivalent complex function; wherein the variables of the equivalent complex function are the predetermined active power and reactive power of the photovoltaic system with an unknown structure; finally, obtaining the Taylor series expansion of the equivalent complex function, and predicting the impedance of the photovoltaic system with an unknown structure through the expansion.

[0061] Compared with the prior art, this application has the following beneficial effects: (1) High efficiency: It avoids repeated impedance scanning for each new working condition, which significantly improves modeling efficiency.

[0062] (2) High precision: By utilizing the mathematical principle of Taylor expansion, high-precision impedance prediction can be achieved near known operating points.

[0063] (3) Practicality: It provides an effective theoretical tool and solution for frequency domain equivalent modeling of black-box photovoltaic systems (photovoltaic systems with unknown structures), which plays an important role in analyzing the grid-connected stability of large-scale photovoltaic fields, especially in early warning of the risk of subsynchronous oscillations caused by photovoltaic grid connection. At the same time, the accurate frequency domain model also provides an important reference for the accuracy of time domain simulation.

[0064] For further explanation of the plan, see Figure 7 The specific implementation of the impedance prediction method for a photovoltaic system with unknown structure provided by the present invention includes the following steps: S1: Establish the parameterized impedance model structure.

[0065] The frequency domain impedance of a photovoltaic (PV) unit at specific P and Q power levels is obtained through impedance scanning and represented as a complex function with P and Q as variables. The basic form of this function is:

[0066] in, , , , , , , , , , , , , , .

[0067] Then, After eliminating the imaginary number from the middle denominator, we can finally obtain:

[0068] in, , , , , , .

[0069] in, It is a stator inductor. It is a magnetizing inductor. For magnetic linkage, This is the sinusoidal angular frequency on the stator side. For the electric angle; The output phase angle of the phase-locked loop (PLL); the PLL transfer function is... ; , This is a reference value for the rotor-side current; , This is a reference value for the grid-side current; , For the rotor side Shaft current measurement value; , For the net side Shaft current measurement value; This refers to the rotor current. Voltage regulation for the rotor-side converter; Voltage modulation for grid-side converter This is the DC bus voltage; This refers to the three-phase output voltage of the stator. and This represents the d-axis and q-axis components of the three-phase output voltage of the machine-side converter in a synchronous rotating coordinate system. This is the three-phase current output by the machine-side converter; and These are the d-axis and q-axis components of the three-phase output current of the machine-side converter in the synchronous rotating coordinate system, respectively. and The three-phase regulation system of the machine-side converter is respectively d-axis and q-axis components in a synchronously rotating coordinate system; It is a PI controller for the current of the machine-side converter. This refers to the three-phase output current of the grid-side converter. and These represent the three-phase regulation of the grid-side converter in a synchronous rotating coordinate system. The d-axis and q-axis are divided; and These represent the d-axis and q-axis values ​​of the three-phase output current of the machine-side converter in a synchronous rotating coordinate system, respectively. It is a PI controller for the grid-side converter current.

[0070] S2: Solve for the derivatives of the model coefficients with respect to power.

[0071] remember Taking the first and second derivatives of P with respect to the real and imaginary parts respectively, we get:

[0072] in, , , , , , , , , , , , , , ..., ,…

[0073] S3: Predict the impedance of unknown operating conditions based on Taylor expansion.

[0074] Using the derivative obtained in step S2, the photovoltaic unit is used to achieve an unknown target power. P Impedance at 0 Z ( P 0) Around a known power point P k Perform a Taylor series expansion. Its expression is:

[0075] By extracting the first few terms of the expansion (such as up to the second-order terms), it is possible to achieve the following: P High-precision prediction of zero-point impedance.

[0076] In the specific implementation process, at least one benchmark operating condition must first be obtained through simulation or experimentation. P k , Q The complete impedance-frequency curve under the given conditions is obtained. Then, based on the model structure established in step S1, the impedance-frequency curve under the given conditions is determined through curve fitting or other parameter identification methods. k Series coefficients. Next, calculate the coefficients at that point according to the formula in step S2. P The derivatives of each order. Finally, for any given new active power setpoint. P 0. Using the Taylor expansion formula from step S3, the predicted impedance value under this new operating condition can be calculated. The core of this method lies in using mathematical analytical derivation to locally linearize or quadraticize the relationship between impedance and power.

[0077] As described above, the specific embodiments of the present invention provide an impedance prediction method for a photovoltaic system with an unknown structure. First, a disturbance signal is injected into a predetermined stable operating point of the photovoltaic system with an unknown structure to generate a frequency impedance curve of the stable operating point; wherein, the frequency of the disturbance signal is determined by the power frequency of the photovoltaic system with an unknown structure; next, the frequency impedance curve is converted into an equivalent complex function; wherein, the variables of the equivalent complex function are the pre-determined active power and reactive power of the photovoltaic system with an unknown structure; finally, the Taylor series expansion of the equivalent complex function is obtained, and the impedance of the photovoltaic system with an unknown structure is predicted by the expansion.

[0078] Specifically, the method provided in this invention first constructs the impedance model of the photovoltaic unit as an explicit complex function of active power P and reactive power Q, and derives analytical expressions for the first and higher-order partial derivatives of this impedance function with respect to power P. Finally, using the Taylor series expansion method, the impedance prediction problem at any target operating point is transformed into a calculation problem based on the known impedance at the operating point and its derivatives. Compared with the prior art, this application has the following beneficial effects: (1) High efficiency: It avoids repeated impedance scanning for each new working condition, which significantly improves modeling efficiency.

[0079] (2) High precision: By utilizing the mathematical principle of Taylor expansion, high-precision impedance prediction can be achieved near known operating points.

[0080] (3) Practicality: It provides an effective theoretical tool and solution for frequency domain equivalent modeling of black-box photovoltaic systems (photovoltaic systems with unknown structures), which plays an important role in analyzing the grid-connected stability of large-scale photovoltaic fields, especially in early warning of the risk of subsynchronous oscillations caused by photovoltaic grid connection. At the same time, the accurate frequency domain model also provides an important reference for the accuracy of time domain simulation.

[0081] Based on the same inventive concept, this application also provides an impedance prediction device for photovoltaic systems with unknown structures, which can be used to implement the methods described in the above embodiments, as shown in the following embodiments. Since the principle of solving the problem in the impedance prediction device for photovoltaic systems with unknown structures is similar to that of the impedance prediction method for photovoltaic systems with unknown structures, the implementation of the impedance prediction device for photovoltaic systems with unknown structures can refer to the implementation of the impedance prediction method for photovoltaic systems with unknown structures, and repeated details will not be elaborated further. As used below, the terms "unit" or "module" can refer to a combination of software and / or hardware that implements a predetermined function. Although the system described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0082] The embodiments of the present invention provide a specific implementation of an impedance prediction device for photovoltaic systems with unknown structures, capable of realizing an impedance prediction method for photovoltaic systems with unknown structures. See [link to specific implementation details]. Figure 8 An impedance prediction device for a photovoltaic system with an unknown structure specifically includes the following components: The frequency impedance curve generation module 10 is used to inject a disturbance signal at a predetermined stable operating point of a photovoltaic system with unknown structure, and generate the frequency impedance curve of the stable operating point; wherein, the frequency of the disturbance signal is determined by the power frequency of the photovoltaic system with unknown structure. The frequency impedance curve conversion module 20 is used to convert the frequency impedance curve into an equivalent complex function; wherein, the variables of the equivalent complex function are the active power and reactive power of the photovoltaic system with unknown structure. The Taylor series expansion module 30 is used to obtain the Taylor series expansion of the equivalent complex function and predict the impedance of the photovoltaic system with unknown structure using the expansion.

[0083] In some embodiments of this application, the disturbance signal is a voltage sequence with a preset amplitude; see also Figure 9 The frequency impedance curve generated in the frequency impedance curve generation module 10 for the stable operating point includes: The current change measurement unit 10a is used to measure the current change of a photovoltaic system with an unknown structure caused by the injection of the disturbance signal; The frequency impedance curve generation unit 10b is used to generate the frequency impedance curve based on the voltage sequence and the current change.

[0084] In some embodiments of this application, see Figure 10 The frequency impedance curve conversion module 20 includes: The complex frequency determination unit 20a is used to determine the real angular frequency and complex frequency of the equivalent complex variable function based on the frequency impedance curve. The transfer function generation unit 20b is used to generate a transfer function based on the complex frequency and the real angular frequency. The equivalent complex function generation unit 20c is used to perform a Laplace transform on the transfer function to generate the equivalent complex function.

[0085] In some embodiments of this application, the complex frequency is used to characterize the amplitude variation of the disturbance signal; see also Figure 11 The complex frequency determination unit 20a includes: Frequency impedance curve characteristic determination unit 20a1 is used to determine the poles, inflection points and slope of the frequency impedance curve. The complex frequency determination subunit 20a2 is used to determine the real angular frequency and the complex frequency based on the frequency impedance curves corresponding to the poles and the inflection points, as well as the slope.

[0086] In some embodiments of this application, see Figure 12 An impedance prediction device for a photovoltaic system with an unknown structure further includes: Stable operating point determination module 40, used to determine the stable operating point; see also Figure 13 The stable operating point determination module 40 includes: Maximum power point determination unit 40a is used to adjust the operating point of the photovoltaic system with unknown structure and determine the maximum power point of the photovoltaic system with unknown structure. The active power determination unit 40b is used to measure the DC-side power at the maximum power point and determine the active power. The reactive power determination unit 40c is used to determine the reactive power based on the voltage deviation at the grid connection point of the photovoltaic system with unknown structure. The stable operating point unit 40d is used to determine the stable operating point based on the active power and the reactive power.

[0087] In some embodiments of this application, the equivalent complex function is:

[0088] In the formula, The equivalent complex function is... , , , , , , , , , , , , , , For the grid-side filter inductor, R s Here is the grid-side filter resistor, s is the frequency domain, and V is the voltage. dc For DC voltage, N s Let N be the equivalent transfer function of the outer loop of the grid-side converter. r Let be the equivalent transfer function of the inner loop of the grid-side converter. V is the proportional parameter of the phase-locked loop. 1为 Grid-side system voltage, 50Hz The voltage of the photovoltaic electric field. For boost circuit inductance, This refers to the duty cycle of the boost circuit switch.

[0089] This application also provides a specific implementation of an electronic device capable of implementing all steps in the impedance prediction method for photovoltaic systems with unknown structures described above. See [link to implementation details]. Figure 14 The electronic devices specifically include the following: Processor 1201, memory 1202, communications interface 1203, and bus 1204; The processor 1201, memory 1202, and communication interface 1203 communicate with each other via bus 1204; the communication interface 1203 is used to realize information transmission between server-side devices and client-side devices and other related devices. The processor 1201 is used to call the computer program in the memory 1202. When the processor executes the computer program, it implements all the steps in the impedance prediction method for a photovoltaic system with an unknown structure in the above embodiments. For example, when the processor executes the computer program, it implements the following steps: A perturbation signal is injected into a predetermined stable operating point of a photovoltaic system with an unknown structure to generate a frequency impedance curve of the stable operating point; wherein the frequency of the perturbation signal is determined by the power frequency of the photovoltaic system with an unknown structure. The frequency impedance curve is converted into an equivalent complex function; wherein the variables of the equivalent complex function are the active power and reactive power of the photovoltaic system with unknown structure. The Taylor series expansion of the equivalent complex function is obtained, and the impedance of the photovoltaic system with unknown structure is predicted using the expansion.

[0090] Embodiments of this application also provide a computer-readable storage medium capable of implementing all steps of the impedance prediction method for an unknown photovoltaic system in the above embodiments. The computer-readable storage medium stores a computer program that, when executed by a processor, implements all steps of the impedance prediction method for an unknown photovoltaic system in the above embodiments. For example, when the processor executes the computer program, it implements the following steps: Multiple three-phase voltages with different initial disturbance frequencies are injected into the three-phase voltage terminals of the pre-generated photovoltaic unit model to determine the equivalent inductance, equivalent resistance, and equivalent capacitance of the photovoltaic unit model under multiple initial disturbance frequencies. A perturbation signal is injected into a predetermined stable operating point of a photovoltaic system with an unknown structure to generate a frequency impedance curve of the stable operating point; wherein the frequency of the perturbation signal is determined by the power frequency of the photovoltaic system with an unknown structure. The frequency impedance curve is converted into an equivalent complex function; wherein the variables of the equivalent complex function are the active power and reactive power of the photovoltaic system with unknown structure. The Taylor series expansion of the equivalent complex function is obtained, and the impedance of the photovoltaic system with unknown structure is predicted using the expansion.

[0091] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on its differences from other embodiments. In particular, hardware + program embodiments are relatively simple in description because they are fundamentally similar to method embodiments; relevant parts can be referred to the descriptions in the method embodiments.

[0092] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0093] While this application provides method operation steps as shown in the embodiments or flowcharts, more or fewer operation steps may be included based on conventional or non-inventive labor. The order of steps listed in the embodiments is merely one possible execution order among many and does not represent the only execution order. In actual device or client product execution, the method can be executed in the order shown in the embodiments or drawings or in parallel (e.g., in a parallel processor or multi-threaded processing environment).

[0094] For ease of description, the above devices are described in terms of function, divided into various modules. Of course, in implementing the embodiments of this specification, the functions of each module can be implemented in one or more software and / or hardware components, or a module that performs the same function can be implemented by a combination of multiple sub-modules or sub-units. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division; 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, or indirect coupling or communication connection between devices or units, and may be electrical, mechanical, or other forms.

[0095] Those skilled in the art will also know that, besides implementing the controller using purely computer-readable program code, the same functions can be achieved by logically programming the method steps, making the controller function as logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers (PLCs), and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the devices within it used to implement various functions can also be considered structures within that hardware component. Alternatively, the devices used to implement various functions can be considered as both software modules implementing the method and structures within a hardware component.

[0096] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0097] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0098] The embodiments described in this specification can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. The embodiments of this specification can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0099] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, system embodiments are basically similar to method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. In the description of this specification, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the embodiments in this specification. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described can be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0100] The above description is merely an embodiment of the present specification and is not intended to limit the embodiments of the present specification. For those skilled in the art, various modifications and variations can be made to the embodiments of the present specification. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of the embodiments of the present specification should be included within the scope of the claims of the embodiments of the present specification.

Claims

1. A method for impedance prediction of a photovoltaic system with unknown structure, characterized in that, include: A disturbance signal is injected into a predetermined stable operating point of a photovoltaic system with an unknown structure to generate a frequency impedance curve of the stable operating point; wherein the frequency of the disturbance signal is determined by the power frequency of the photovoltaic system with an unknown structure. The frequency impedance curve is converted into an equivalent complex function; wherein the variables of the equivalent complex function are the active power and reactive power of the photovoltaic system with unknown structure. The Taylor series expansion of the equivalent complex function is obtained, and the impedance of the photovoltaic system with unknown structure is predicted using the expansion.

2. The impedance prediction method according to claim 1, characterized in that, The disturbance signal is a voltage sequence with a preset amplitude. Generating the frequency impedance curve of the stable operating point includes: Measure the current change in a photovoltaic system with an unknown structure caused by the injection of the disturbance signal; The frequency impedance curve is generated based on the voltage sequence and the current change.

3. The impedance prediction method according to claim 1, characterized in that, Converting the frequency impedance curve into an equivalent complex function includes: The real angular frequency and complex frequency of the equivalent complex function are determined based on the frequency impedance curve. A transfer function is generated based on the complex frequency and the real angular frequency; The transfer function is subjected to a Laplace transform to generate the equivalent complex function.

4. The impedance prediction method according to claim 3, characterized in that, The complex frequency is used to characterize the amplitude change of the disturbance signal; determining the real angular frequency and complex frequency of the equivalent complex function based on the frequency impedance curve includes: Determine the poles, inflection points, and slope of the frequency impedance curve; The real angular frequency and the complex frequency are determined based on the frequency impedance curves corresponding to the poles and inflection points, as well as the slope.

5. The impedance prediction method according to claim 1, characterized in that, The steps for determining the stable operating point include: Adjust the operating point of the photovoltaic system with unknown structure to determine the maximum power point of the photovoltaic system with unknown structure; Measure the DC-side power at the maximum power point to determine the active power; The reactive power is determined based on the voltage deviation at the grid connection point of the photovoltaic system with unknown structure. The stable operating point is determined based on the active power and the reactive power.

6. The impedance prediction method according to any one of claims 1 to 5, characterized in that, The equivalent complex function is: In the formula, The equivalent complex function is... , , , , , , , , , , , , , , For the grid-side filter inductor, R s Here is the grid-side filter resistor, s is the frequency domain, and V is the voltage. dc For DC voltage, N s Let N be the equivalent transfer function of the outer loop of the grid-side converter. r Let be the equivalent transfer function of the inner loop of the grid-side converter. V is the proportional parameter of the phase-locked loop. 1为 Grid-side system voltage, 50Hz The voltage of the photovoltaic electric field. For boost circuit inductance, This refers to the duty cycle of the boost circuit switch.

7. An impedance prediction device for a photovoltaic system with an unknown structure, characterized in that, include: A frequency impedance curve generation module is used to inject a disturbance signal into a predetermined stable operating point of a photovoltaic system with an unknown structure, and generate a frequency impedance curve of the stable operating point; wherein the frequency of the disturbance signal is determined by the power frequency of the photovoltaic system with an unknown structure. A frequency impedance curve conversion module is used to convert the frequency impedance curve into an equivalent complex function; wherein the variables of the equivalent complex function are the active power and reactive power of the photovoltaic system with unknown structure. The Taylor series expansion module is used to obtain the Taylor series expansion of the equivalent complex function and predict the impedance of the photovoltaic system with unknown structure using the expansion.

8. A computer program product comprising a computer program / instructions, characterized in that, When executed by a processor, the computer program / instructions implement the steps of the impedance prediction method for an unknown photovoltaic system as described in any one of claims 1 to 6.

9. An electronic device 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 program, it implements the steps of the impedance prediction method for a photovoltaic system with an unknown structure as described in any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the impedance prediction method for an unknown photovoltaic system as described in any one of claims 1 to 6.

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