Power system off-line inertia identification method and device based on frequency response model

Abstract

The invention relates to a power system off-line inertia identification method and device based on a frequency response model, and the method comprises the steps: obtaining a frequency response curve of a power system; identifying a frequency curve by using a pre-constructed frequency response model and the frequency response curve; and obtaining the frequency change rate of the system at the disturbance occurrence moment of the power system according to the frequency curve so as to calculate the off-line inertia of the power system. According to the embodiment of the invention, by establishing the frequency response model considering the synchronous generator, the new energy, the load and other equipment, on the basis of the dynamic synchronous phasor algorithm, the influence of the measurement noise on the inertia evaluation is effectively reduced, a new theoretical basis and a technical means are provided for the system node inertia evaluation, and the system node inertia evaluation efficiency is improved. Furthermore, the method is expanded to a multi-machine system, a beneficial reference is provided for research in the field of inertia evaluation of the power system, and a theoretical support and a technical means are provided for improving the operation reliability of the power system.

Description

Technical Field

[0001] This application relates to the technical field of offline inertia identification of single-machine systems, and particularly relates to a method and device for offline inertia identification of a power system based on a frequency response model. Background Art

[0002] With the access of a large number of new energy and power electronic devices to the distribution network, the power system is gradually showing characteristics such as low inertia and underdamping. Inertia is an inherent property of the power system, which is reflected as the resistance of the system to external energy fluctuations to maintain the frequency stability of the system. Currently, energy storage, new energy devices, and network-forming converters such as virtual synchronous generators (VSGs) all have the ability to support virtual inertia. In the future, a large number of such devices will be connected to the distribution network. Therefore, their inertia values can be adjusted in real time through parameter settings. In order to maintain the frequency safety of the system, it is necessary to evaluate the inertia support ability of the substation area for the upper-level distribution network, that is, to accurately evaluate the equivalent inertia of the grid-connected node.

[0003] Currently, scholars have conducted a lot of research on inertia evaluation methods. Online evaluation methods are based on smart grid technologies such as synchronized wide-area measurement, which can measure time-varying inertia data. They have high requirements for the real-time performance of algorithms and are easily affected by problems such as measurement noise and communication delay, resulting in insufficient identification accuracy. Offline identification cannot measure real-time inertia changes, but it can be analyzed based on historical data filtering, and the results are more stable. Moreover, it does not require high-precision measurement devices and communication devices, and the construction and operation and maintenance costs are significantly lower than those of online identification. The offline inertia evaluation method based on frequency events was proposed in 1997. It obtains the rate of change of frequency (RoCoF) data of the system at the moment of disturbance based on frequency measurement, and calculates the total inertia size of the system through the rotor motion equation. This method requires a small amount of data and is easy to calculate. It only requires power disturbance amounts and frequency data at the moment of disturbance, so it is often applied to various scenarios of inertia estimation and virtual inertia control. A measurement-driven method based on the second derivative of frequency in synchronized phasor data is used to quickly and accurately estimate the frequency response under large-scale power system disturbances. Based on the synchronized phasor measurement device, a moving average filter is used to reduce the measurement error of the rate of change of frequency, and it is pointed out that interval oscillation will cause the RoCoF measurement to be inaccurate. Over the years, scholars have continuously devoted themselves to the research of offline inertia evaluation, but the difficulty still lies in how to determine the size of the system disturbance power and the accurate measurement of RoCoF.

[0004] The phase-locked loop (PLL) is the most commonly used means to calculate the frequency of a computing node. It can obtain the frequency curve and get the RoCoF value through the differentiation of the frequency. However, when the system is disturbed, the inertia calculation only requires the frequency value at the initial moment of the disturbance. Since the PLL itself is in a dynamic process and has not yet stabilized, it is difficult to accurately track the change of the system frequency, and the measurement accuracy of the virtual inertia is poor. In addition, the synchronous phasor algorithm is also a commonly used means to measure the system frequency. The synchronous phasor algorithm based on the static phasor model can only track slow frequency offsets, and its tracking effect for the instantaneous RoCoF under frequency mutations is poor. While using the dynamic synchronous phasor algorithm can improve the accuracy of frequency measurement. At present, some studies have effectively improved the measurement accuracy and dynamic frequency measurement ability of the synchronous phasor algorithm based on optimal filter design or adaptive synchronous phasors. However, since the synchronous phasor algorithm still has a relatively short transient process, its accuracy still has certain limitations in scenarios where the rate of change of frequency at the moment of disturbance needs to be accurately calculated for inertia calculation.

[0005] In the current distribution network with a high proportion of power electronic devices and new energy access, in addition to synchronous generators, power electronic devices, and new energy generation units on the power generation side, the dynamic behavior on the load side will also affect the system frequency characteristics. A system frequency response model considering various devices needs to be established urgently. In addition, when there are multiple generators in the system, power transfer and power oscillation phenomena may occur during the transient process after the disturbance. At this time, the frequency response form of the nodes in the system will be more complex, showing an oscillation mode superimposed by multiple oscillation modes, making it more difficult to model the frequency curve. Compared with traditional methods, how to accurately measure the RoCoF and thus accurately calculate the inertia of the multi-machine system is also a problem that needs to be studied. Summary of the Invention

[0006] This application provides a method and device for offline inertia identification of a power system based on a frequency response model to solve the problems in the related art, such as insufficient accuracy of power system inertia measurement and evaluation, and limitations of the PLL measurement link and the conventional dynamic synchronous phasor algorithm in inertia calculation.

[0007] The first aspect embodiment of this application provides a method for offline inertia identification of a power system based on a frequency response model, including the following steps: obtaining the frequency response curve of the power system; identifying the frequency curve by using a pre-constructed frequency response model and the frequency response curve; obtaining the rate of change of the system frequency at the moment of disturbance of the power system according to the frequency curve to calculate the offline inertia of the power system.

[0008] Optionally, in an embodiment of this application, the single-machine frequency response identification model of the frequency response model is:

[0009]

[0010] Among them, p1 is the steady-state part parameter corresponding to the two-part oscillation, and p2, p3, p4, and p5 are all parameters corresponding to the single-machine inertia response model.

[0011] Optionally, in an embodiment of the present application, the inter-machine oscillation model of the frequency response model is:

[0012]

[0013] Among them, p1 is the steady-state part parameter corresponding to the two-part oscillation, p2, p3, p4, and p5 are all parameters corresponding to the single-machine inertia response model, and p6, p7, p8, and p9 are all parameters corresponding to the inter-machine oscillation model.

[0014] Optionally, in an embodiment of the present application, obtaining the system frequency change rate at the moment of power system disturbance occurrence according to the frequency curve includes: identifying the frequency component of the single-machine response; using the frequency component of the single-machine response to identify the frequency component of the inter-machine oscillation, so as to combine the frequency component of the single-machine response and the frequency component of the inter-machine oscillation to obtain the final frequency result; obtaining the frequency change rate based on the frequency curve and the final frequency result.

[0015] An embodiment of the second aspect of the present application provides a power system off-line inertia identification device based on a frequency response model, including: an acquisition module for acquiring the frequency response curve of the power system; an identification module for identifying the frequency curve by using a pre-constructed frequency response model and the frequency response curve; a calculation module for obtaining the system frequency change rate at the moment of power system disturbance occurrence according to the frequency curve to calculate the off-line inertia of the power system.

[0016] Optionally, in an embodiment of the present application, the single-machine frequency response identification model of the frequency response model is:

[0017]

[0018] Among them, p1 is the steady-state part parameter corresponding to the two-part oscillation, and p2, p3, p4, and p5 are all parameters corresponding to the single-machine inertia response model.

[0019] Optionally, in an embodiment of the present application, the inter-machine oscillation model of the frequency response model is:

[0020]

[0021] Among them, p1 is the steady-state part parameter corresponding to the oscillation of the two parts, p2, p3, p4, and p5 are all parameters corresponding to the single-machine inertia response model, and p6, p7, p8, and p9 are all parameters corresponding to the inter-machine oscillation model.

[0022] Optionally, in an embodiment of the present application, the calculation module includes: a first identification unit for identifying the frequency component of the single-machine response; a second identification unit for identifying the frequency component of the inter-machine oscillation by using the frequency component of the single-machine response, so as to obtain a final frequency result by combining the frequency component of the single-machine response and the frequency component of the inter-machine oscillation; and a generation unit for obtaining the frequency change rate based on the frequency curve and the final frequency result.

[0023] An embodiment of the third aspect of the present application provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor executes the program to implement the power system offline inertia identification method based on the frequency response model as described in the above embodiment.

[0024] An embodiment of the fourth aspect of the present application provides a computer-readable storage medium, and the computer-readable storage medium stores a computer program, and when the program is executed by a processor, it implements the power system offline inertia identification method based on the frequency response model as described above.

[0025] An embodiment of the fifth aspect of the present application provides a computer program product, and the computer program product stores a computer program, and when the program is executed by a processor, it implements the power system offline inertia identification method based on the frequency response model as described above.

[0026] By establishing a frequency response model considering devices such as synchronous generators, new energy, and loads in the embodiments of the present application, on the basis of the dynamic synchronous phasor algorithm, a single-machine system inertia identification method based on the frequency response model is proposed, which effectively reduces the influence of measurement noise on inertia assessment, provides a new theoretical basis and technical means for system node inertia assessment, further extends this method to a multi-machine system, and proposes a multi-machine system inertia identification method based on the frequency response model, providing a useful reference for the research in the field of power system inertia assessment and providing theoretical support and technical means for improving the operation reliability of the power system. Thus, the problems in the related technologies, such as the insufficient accuracy of power system inertia measurement and assessment, and the limitations of the phase-locked loop measurement link and the conventional dynamic synchronous phasor algorithm in inertia calculation, are solved.

[0027] The additional aspects and advantages of the present application will be partially given in the following description, partially become obvious from the following description, or be understood through the practice of the present application. Description of the Drawings

[0028] The above and / or additional aspects and advantages of the present application will become apparent and be readily understood from the following description of embodiments in conjunction with the accompanying drawings, where:

[0029] Figure 1 FIG. is a flowchart of a method for offline inertia identification of a power system based on a frequency response model according to an embodiment of the present application;

[0030] Figure 2 FIG. is a flowchart for identifying an inertia response model of a single-machine system according to an embodiment of the present application;

[0031] Figure 3 FIG. is a schematic diagram of a single fitting result of a system with power oscillation according to an embodiment of the present application;

[0032] Figure 4 FIG. is a schematic diagram of the identification process of an inertia response model of a single-machine system according to an embodiment of the present application;

[0033] Figure 5 FIG. is a schematic structural diagram of an offline inertia identification device for a power system based on a frequency response model according to an embodiment of the present application;

[0034] Figure 6 FIG. is a schematic structural diagram of an electronic device according to an embodiment of the present application. Detailed Embodiments

[0035] Embodiments of the present application will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to explain the present application and should not be construed as limiting the present application.

[0036] The off-line inertia identification method and device of a power system based on a frequency response model according to an embodiment of the present application will be described below with reference to the accompanying drawings. In view of the problems in the related art mentioned in the above background art, that is, the accuracy of power system inertia measurement and evaluation is insufficient, and there are limitations in the inertia calculation in the phase-locked loop measurement link and the conventional dynamic synchronous phasor algorithm, the present application provides an off-line inertia identification method of a power system based on a frequency response model. In this method, by establishing a frequency response model considering devices such as synchronous generators, new energy, and loads, on the basis of the dynamic synchronous phasor algorithm, a single-machine system inertia identification method based on the frequency response model is proposed, which effectively reduces the influence of measurement noise on inertia evaluation, provides a new theoretical basis and technical means for system node inertia evaluation, further extends this method to a multi-machine system, and proposes a multi-machine system inertia identification method based on the frequency response model, which provides a useful reference for the research in the field of power system inertia evaluation and provides theoretical support and technical means for improving the operation reliability of the power system. Thus, the problems in the related art, such as insufficient accuracy of power system inertia measurement and evaluation and limitations in the inertia calculation in the phase-locked loop measurement link and the conventional dynamic synchronous phasor algorithm, are solved.

[0037] Specifically, Figure 1 is a schematic flowchart of an off-line inertia identification method of a power system based on a frequency response model provided by an embodiment of the present application.

[0038] As Figure 1 shown, the off-line inertia identification method of the power system based on the frequency response model includes the following steps:

[0039] In step S101, obtain the frequency response curve of the power system.

[0040] In the actual execution process, the embodiment of the present application can obtain the frequency response curve of the power system, so as to provide support for subsequent identification of the system inertia, and further provide a useful reference for the research in the field of power system inertia evaluation and provide theoretical support and technical means for improving the operation reliability of the power system.

[0041] In step S102, use the pre-constructed frequency response model and the frequency response curve to identify the frequency curve.

[0042] It can be understood that the pre-constructed frequency response model in the embodiment of the present application can be a frequency response model considering devices such as synchronous generators, new energy, and loads.

[0043] This application can perform device frequency response model modeling. To accurately characterize the dynamic characteristics of various devices in the power system and achieve precise identification of node inertia, this application further analyzes the frequency response models of key devices in the system. In a distribution network with a high proportion of power electronic devices and new energy access, the generating devices include synchronous generators, power electronic devices, new energy generation units, etc. At the same time, the frequency response dynamics on the load side will also affect the system frequency characteristics. This application establishes the frequency response models of different devices such as each generating unit and complex loads respectively to comprehensively reflect the contributions of various devices in the system frequency dynamic process.

[0044] When considering a synchronous generator, the active-power frequency transfer function of a single-machine system is shown in Equation (1). The model ignores the non-linearity and all time constants except the largest time constant, and can be used to estimate the frequency response behavior of the power system to sudden load disturbances, with high accuracy.

[0045]

[0046] When a step power disturbance of magnitude ΔP occurs in the single-machine system, at this time ΔP e (s)=ΔP / s, and the single-machine frequency response of the system is shown in Equation (2).

[0047]

[0048]

[0049] Among them, R is the governor speed regulation gain, K m is the mechanical power gain coefficient, and the natural oscillation frequency ω n , damping ratio ζ, damped oscillation frequency, and α coefficient, etc. are calculated according to the system parameters and are fixed values under the fixed operating mode of the system. Therefore, in the system identification model, they can be simplified and represented by a single constant:

[0050]

[0051] Among them, p1 - p5 are the coefficients to be identified, and the power disturbance occurs at time t0.

[0052] Furthermore, in the new power system of this application embodiment, the control strategy of power electronic devices (such as grid-connected converters) has an important impact on the system frequency response. According to different control methods, power electronic devices are mainly divided into grid-following control (GFL) and grid-forming control (GFM).

[0053] Power electronic devices with network-forming control (such as energy storage inverters and virtual synchronous machines) can simulate the characteristics of synchronous generators, actively provide frequency and voltage support, and can provide virtual inertia for the system.

[0054] The network-forming control uses a virtual inertia link to simulate the rotor motion equation of a synchronous generator, and its dynamic characteristics can be expressed as:

[0055]

[0056] where H is the virtual inertia constant and D is the damping coefficient.

[0057] The primary frequency regulation simulates the function of the governor of a synchronous generator and usually uses P-ω droop control:

[0058] ΔP m =K f Δω, (6)

[0059] where K f is the active-power - frequency droop coefficient.

[0060] The frequency response model of the network-forming device can be expressed as the combination of a virtual inertia link and a droop control link:

[0061]

[0062] At this time, the role of the droop coefficient K f is similar to that of the damping D and does not affect the inertia H of the device. The two can be equivalently treated. Therefore, when a power disturbance of ΔP magnitude occurs in a single-machine system, the frequency response model of the network-forming device under the disturbance is as follows:

[0063]

[0064] At the same time, some virtual synchronous controls simulate the mechanical response delay of the governor, or their input power is affected by the power characteristics of the previous-stage energy storage, etc., which is manifested as a lag process of power adjustment. A first-order inertia link must be added on the basis of the droop control, as shown in Equation (9):

[0065]

[0066] At this time, the transfer function of the network-forming control can be derived:

[0067]

[0068] Therefore, when a power disturbance of ΔP magnitude occurs in a single-machine system, the single-machine frequency response of the system is calculated, as shown in Equation (11):

[0069]

[0070] According to the above analysis, the single-machine frequency response models of equations (8) and (11) can both be regarded as special cases of equation (2) with different partial parameters. That is, regardless of whether the first-order inertia link is considered, the single-machine frequency response model of the network-forming equipment can be described by equation (2).

[0071] When considering equipment such as new energy and loads, different from traditional synchronous generators, grid-following control usually needs to quickly respond to grid changes and generate active power through control. Grid-following control can only passively track the grid frequency, and its output power does not respond to system frequency changes and cannot provide inertia support for the system. Currently, most new energy equipment still adopts conventional grid-following control strategies, and their inertia contributions can often be ignored.

[0072] However, to improve grid stability, some grid-following inverters have achieved frequency regulation functions through additional control strategies. For example, by simulating the frequency-power droop characteristics of synchronous generators, as shown in equation (13), the output power is adjusted proportionally according to the grid frequency deviation, and it has been applied in some photovoltaic power stations and energy storage converters. The control monitors the grid frequency in real time, feeds the frequency signal back to the power regulation module of the converter, and finally outputs transient active power associated with the frequency change rate through dynamic correction of the active power reference value. The expression is:

[0073] ΔP GFL =K GFL Δω, (13)

[0074] where K GFL is the droop control coefficient.

[0075] Grid-following control short-term changes the output power by measuring the frequency, but its essence is still power response, and it does not increase the magnitude of the system equivalent inertia value and will not affect the system inertia characteristics.

[0076] When constructing the load frequency response model, the load composition in the system is complex and the load distribution is scattered. The load power changes with voltage and frequency. The most commonly used static load model is the composite load polynomial model, which includes three types of loads: constant impedance, constant current, and constant power (ZIP model). When considering the frequency influence on this basis, the static active load model is as shown in equation (14):

[0077]

[0078] where U0 is the reference voltage, P0 is the load power when the voltage is U0, a, b, c are the proportions of various loads, and L DP is the active frequency influence factor.

[0079] When studying the system frequency characteristics, it is generally considered that the load voltage remains unchanged, that is, the change in power is proportional to the change in frequency. After sorting, it can be obtained:

[0080] ΔP L = K L Δω, (15)

[0081] Therefore, the load characteristics are similar to those of the grid-following devices with frequency regulation characteristics. Conducting power response to frequency will affect the frequency characteristics of the system, without increasing the magnitude of the system equivalent inertia value and having no impact on the system inertia characteristics.

[0082] Furthermore, when constructing the frequency response model of a single-machine system, without considering the load frequency regulation effect, the frequency response characteristics of the single-machine power system can be characterized by the dynamic model described in Equation (1). However, when the synchronous generator is connected to loads and grid-following devices with frequency regulation capabilities, the characteristics of the synchronous machine and the frequency characteristics of the loads and grid-following devices need to be considered to establish the frequency response model of the single-machine system.

[0083] Assume that there is a power disturbance ΔP in the system d , and the system power dynamic characteristic equation is:

[0084]

[0085] The form of the frequency dynamic equation is consistent with the synchronous machine rotor motion equation shown in Equation (5), where the control coefficients of the load and grid-following devices can be incorporated into the synchronous machine damping term D. Thus, when the system generates a step power disturbance of magnitude ΔP, after arrangement, the frequency response model is similar to the frequency characteristic expression (1) of the synchronous machine, except that the equivalent damping coefficient incorporates the coefficients of the load and grid-following devices, and the result is as shown in Equation (17):

[0086]

[0087] During a step power disturbance, ΔP d (s) = ΔP / s. Substituting this into the above equation gives the single-machine frequency response of the system as shown in Equation (18):

[0088]

[0089] Based on the above analysis, the frequency response model forms shown in Equation (18) and Equation (2) are the same, with only parameters such as D′, ω′ n , ω′ r , ζ′, α′, etc. changing. However, under the fixed operating mode of the system, it can still be simplified and represented by a single constant. Therefore, when constructing the frequency response characteristics of various types of power generation equipment in the system, including synchronous machines and network-forming converters, even considering the network-forming converters and loads, the frequency response model shown in Equation (4) can be used to summarize and describe them during disturbances. Next, establish the complete single-machine system frequency response model before and after the disturbance.

[0090] It is considered that the system frequency is stable before the disturbance, that is, the frequency is represented by a straight line f = f0. To accurately obtain the frequency change rate at the initial moment of the disturbance, it is necessary to make the model smooth before and after the disturbance occurs. That is, at the moment of the disturbance t = t0, the frequencies in the two expressions are made equal, that is:

[0091] f0 = p1 + p2sin(p5), (20)

[0092] Optionally, in an embodiment of the present application, the complete single-machine frequency response identification model is sorted out. That is, the single-machine frequency response identification model of the frequency response model is:

[0093]

[0094] Among them, p1 is the steady-state part parameter corresponding to the two parts of the oscillation, and p2, p3, p4, and p5 are all the corresponding parameters of the single-machine inertia response model.

[0095] In the actual execution process, after the frequency response curve of the single-machine system is obtained in the embodiment of the present application, the system inertia can be identified by using the frequency response model of formula (21). As shown in (22), the trust-region reflection algorithm in the nonlinear least squares method is used. This is an advanced numerical optimization method for minimizing the sum of squared residuals in nonlinear model fitting.

[0096]

[0097] Among them, f is the frequency measured by the DPEFM method, is the frequency response model of formula (21), and p1 - p5 are the coefficients to be identified.

[0098] Then, the RoCoF value of the system is obtained by differentiating the identified frequency curve. Here, two methods can be used to calculate the RoCoF. One method is to use numerical differentiation. Since the identification model has excluded noise interference, numerical differentiation can be directly performed, and the obtained frequency change rate result is also relatively smooth. The other is to directly represent the initial value of the RoCoF by the identified parameters, that is:

[0099]

[0100] After simulation verification, the results obtained by the two methods are basically the same. For the convenience of calculation, the direct numerical differentiation method is used in this article for calculation, and the system inertia is calculated using the RoCoF initial value, as shown in formula (25). The identification process of the single-machine system inertia response model is as Figure 2 shown.

[0101]

[0102] Aiming at the problem of insufficient accuracy in the measurement and evaluation of the inertia of the power system, the limitations of the phase-locked loop measurement link and the conventional dynamic synchronous phasor algorithm in inertia calculation are analyzed. By establishing a frequency response model considering equipment such as synchronous generators, new energy, and loads, based on the dynamic synchronous phasor algorithm, a single-machine system inertia identification method based on the frequency response model is proposed, which effectively reduces the influence of measurement noise on inertia evaluation, and provides a new theoretical basis and technical means for the inertia evaluation of system nodes. It is used for the offline identification of the inertia of the single-machine system, which can effectively eliminate the noise interference in the measurement link, provides a new theoretical basis and technical means for the inertia evaluation of system nodes, and is extended to the multi-machine system. A multi-machine system inertia identification method based on the frequency response model is proposed, providing a useful reference for the research in the field of power system inertia evaluation.

[0103] In step S103, according to the frequency curve, the rate of change of the system frequency at the moment of power system disturbance is obtained to calculate the offline inertia of the power system.

[0104] It can be understood that when there are multiple machines in the system and the inertia of a certain node needs to be calculated, a power disturbance needs to be applied to this node, and the initial value of the RoCoF of this node is measured.

[0105] In the actual execution process, the embodiment of the present application can obtain the rate of change of the system frequency at the moment of power system disturbance according to the frequency curve to calculate the offline inertia of the power system. When there are n generators in the system, after a power disturbance occurs in the system, the power of each generator at the moment of disturbance and the terminal frequency of the machine are determined by the disturbance position and the inertia of the unit, while the steady-state power of the unit and the terminal frequency of the machine after the disturbance are determined by the primary frequency modulation coefficient. During this transition process, there will be power transfer and power oscillation between the units. That is, in a multi-machine system, power oscillation will occur between multiple generators, and a system with n generators may have n - 1 oscillation modes. The multi-machine oscillation will cause fluctuations in the frequency curve, and it cannot be accurately described by only the single-machine response oscillation model.

[0106] When there are two generators in the system, after a disturbance occurs at a certain point in the system, the system voltage curve is measured at the terminal of generator 1, and the system frequency curve is obtained through synchronous phasor calculation and modeling identification methods, and compared with the actual rotor frequency inside the generator. The results are as Figure 3 shown. It can be seen that the curve obtained by using the single identification method is equivalent to the average change curve of the actual frequency response, but it cannot describe the frequency fluctuation term caused by the power oscillation between the generators, which will bring errors to the measurement of the initial frequency change rate and the inertia calculation. Therefore, it is necessary to model and describe the multi-machine oscillation part, expand the single-machine response model under disturbance, and add the frequency term of the inter-machine oscillation.

[0107] This application further extends this method to a multi-machine system and proposes an inertia identification method for multi-machine systems based on frequency response models, providing a useful reference for research in the field of power system inertia assessment and providing theoretical support and technical means for improving the operational reliability of power systems.

[0108] Optionally, in an embodiment of this application, in order to simplify the calculation, only the mode with the greatest impact on the system is selected for identification. The inter-machine oscillation is also described in the form of the oscillation model in Equation (21). At this time, the frequency model of inter-machine oscillation is considered, that is, the formula for inter-machine oscillation of the frequency response model is:

[0109]

[0110] where p1 is the steady-state part parameter corresponding to the two parts of oscillation, p2, p3, p4, and p5 are all parameters corresponding to the single-machine inertia response model, and p6, p7, p8, and p9 are all parameters corresponding to the inter-machine oscillation model.

[0111] Optionally, in an embodiment of this application, the rate of change of the system frequency at the moment of power system disturbance is obtained according to the frequency curve, including: identifying the frequency component of the single-machine response; using the frequency component of the single-machine response to identify the frequency component of inter-machine oscillation, so as to combine the frequency component of the single-machine response and the frequency component of inter-machine oscillation to obtain the final frequency result; obtaining the rate of change of frequency based on the frequency curve and the final frequency result.

[0112] It can be understood that since the same form of oscillation model is used to identify the two kinds of oscillations, it will lead to confusion of the identification model and a decline in identification performance. Since the proportion of inter-machine oscillation in the components is relatively small, a step-by-step modeling and identification strategy is selected.

[0113] Specifically, in the embodiment of this application, Equation (21) can still be used to first identify the frequency component of the single-machine response. On the basis of removing this component, Equation (21) is used to identify the part of inter-machine oscillation again. The two results are added to obtain the final frequency result. Then, the RoCoF value of the system is obtained by differentiating the identified frequency curve and substituted back into Equation (25) to calculate the system inertia. The identification process of the multi-machine system inertia response model is as Figure 4 shown.

[0114] The off-line inertia identification method of the power system based on the frequency response model proposed according to the embodiments of the present application establishes a frequency response model considering devices such as synchronous generators, new energy, and loads. On the basis of the dynamic synchronous phasor algorithm, a single-machine system inertia identification method based on the frequency response model is proposed, which effectively reduces the influence of measurement noise on inertia evaluation, provides a new theoretical basis and technical means for system node inertia evaluation, further extends this method to a multi-machine system, and proposes a multi-machine system inertia identification method based on the frequency response model, providing a useful reference for the research in the field of power system inertia evaluation and providing theoretical support and technical means for improving the operation reliability of the power system. Thus, the problems in the related technologies, such as the insufficient accuracy of power system inertia measurement and evaluation, and the limitations of the phase-locked loop measurement link and the conventional dynamic synchronous phasor algorithm in inertia calculation, are solved.

[0115] Next, the off-line inertia identification device of the power system based on the frequency response model proposed according to the embodiments of the present application is described with reference to the accompanying drawings.

[0116] Figure 5 It is a schematic structural diagram of the off-line inertia identification device of the power system based on the frequency response model according to the embodiments of the present application.

[0117] As Figure 5 shown, the off-line inertia identification device 10 of the power system based on the frequency response model includes: an acquisition module 100, an identification module 200, and a calculation module 300.

[0118] Specifically, the acquisition module 100 is used to acquire the frequency response curve of the power system.

[0119] The identification module 200 is used to identify the frequency curve by using the pre-constructed frequency response model and the frequency response curve.

[0120] The calculation module 300 is used to obtain the frequency change rate of the system at the moment of power system disturbance according to the frequency curve, so as to calculate the off-line inertia of the power system.

[0121] Optionally, in an embodiment of the present application, the single-machine frequency response identification model of the frequency response model is:

[0122]

[0123] Wherein, p1 is the steady-state part parameter corresponding to the two-part oscillation, and p2, p3, p4, and p5 are all the parameters corresponding to the single-machine inertia response model.

[0124] Optionally, in an embodiment of the present application, the inter-machine oscillation model of the frequency response model is:

[0125]

[0126] Among them, p1 is the steady-state part parameter corresponding to the oscillation of two parts, p2, p3, p4, and p5 are all parameters corresponding to the single-machine inertia response model, and p6, p7, p8, and p9 are all parameters corresponding to the inter-machine oscillation model.

[0127] Optionally, in an embodiment of the present application, the calculation module 300 includes: a first identification unit, a second identification unit, and a generation unit.

[0128] Among them, the first identification unit is used to identify the frequency component of the single-machine response.

[0129] The second identification unit is used to identify the frequency component of the inter-machine oscillation by using the frequency component of the single-machine response, so as to obtain the final frequency result by combining the frequency component of the single-machine response and the frequency component of the inter-machine oscillation.

[0130] The generation unit is used to obtain the frequency change rate based on the frequency curve and the final frequency result.

[0131] It should be noted that the foregoing explanation of the embodiment of the off-line inertia identification method for a power system based on a frequency response model also applies to the off-line inertia identification device for a power system based on a frequency response model in this embodiment, and will not be elaborated here.

[0132] According to the off-line inertia identification device for a power system based on a frequency response model proposed in the embodiment of the present application, by establishing a frequency response model considering devices such as synchronous generators, new energy, and loads, and on the basis of the dynamic synchronous phasor algorithm, a single-machine system inertia identification method based on a frequency response model is proposed, which effectively reduces the influence of measurement noise on inertia evaluation, provides a new theoretical basis and technical means for system node inertia evaluation, further extends this method to a multi-machine system, and proposes a multi-machine system inertia identification method based on a frequency response model, providing a useful reference for the research in the field of power system inertia evaluation and providing theoretical support and technical means for improving the operation reliability of the power system. Thus, the problems in the related technology that the accuracy of power system inertia measurement and evaluation is insufficient and there are limitations in the inertia calculation in the phase-locked loop measurement link and the conventional dynamic synchronous phasor algorithm are solved.

[0133] Figure 6 This is a schematic structural diagram of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0134] A memory 601, a processor 602, and a computer program stored on the memory 601 and executable on the processor 602.

[0135] When the processor 602 executes the program, it implements the off-line inertia identification method for a power system based on a frequency response model provided in the foregoing embodiment.

[0136] Further, the electronic device further includes:

[0137] A communication interface 603 for communication between the memory 601 and the processor 602.

[0138] A memory 601 for storing computer programs that can run on the processor 602.

[0139] The memory 601 may include a high-speed RAM memory, and may also include non-volatile memory, such as at least one disk memory.

[0140] If the memory 601, the processor 602, and the communication interface 603 are implemented independently, the communication interface 603, the memory 601, and the processor 602 can be interconnected through a bus and complete communication with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of representation, Figure 6 only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus.

[0141] Optionally, in a specific implementation, if the memory 601, the processor 602, and the communication interface 603 are integrated on a chip, the memory 601, the processor 602, and the communication interface 603 can complete communication with each other through an internal interface.

[0142] The processor 602 may be a Central Processing Unit (CPU), or an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0143] This embodiment also provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, it implements the above-mentioned power system offline inertia identification method based on a frequency response model.

[0144] The embodiments of the present application also provide a computer program product, on which a computer program is stored, and when the program is executed by a processor, it implements the above-mentioned power system offline inertia identification method based on a frequency response model.

[0145] In the description of this specification, the descriptions referring to terms such as "one embodiment", "some embodiments", "examples", "specific examples", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0146] In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "N" is at least two, such as two, three, etc., unless otherwise specifically defined.

[0147] Any process or method description shown in the flowchart or described in other ways herein can be understood to represent a module, segment, or portion of code including one or N executable instructions for implementing a customized logic function or process, and the scope of the preferred embodiments of the present application includes additional implementations, where the functions may be executed in a substantially simultaneous manner or in a reverse order according to the involved functions, rather than in the order shown or discussed, which should be understood by those skilled in the art to which the embodiments of the present application pertain.

[0148] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a definable sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch instructions from the instruction execution system, apparatus, or device and execute the instructions), or used in combination with these instruction execution systems, apparatus, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection portion (electronic device) having one or N wirings, a portable computer disk cartridge (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically by optically scanning the paper or other media, followed by editing, interpretation, or otherwise processing as appropriate, and then stored in a computer memory.

[0149] It should be understood that various parts of the present application can be implemented by hardware, software, firmware, or a combination thereof. In the above-described embodiments, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application-specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0150] Those of ordinary skill in the art of this technology can understand that all or part of the steps carried by the method of implementing the above embodiments can be completed by a program instructing relevant hardware, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0151] In addition, each functional unit in various embodiments of the present application may be integrated into a processing module, may exist physically alone for each unit, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0152] The above-mentioned storage medium may be a read-only memory, a magnetic disk, an optical disc, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. An off-line inertia identification method for power systems based on frequency response models, characterized in that, Including the following steps: Obtain the frequency response curve of the power system; Identify the frequency curve by using the pre-constructed frequency response model and the frequency response curve; Obtain the frequency change rate of the system at the moment of disturbance occurrence in the power system according to the frequency curve, so as to calculate the off-line inertia of the power system.

2. The method according to claim 1, wherein The single-machine frequency response identification model of the frequency response model is: where p1 is the steady-state part parameter corresponding to the two-part oscillation, and p2, p3, p4, and p5 are all the corresponding parameters of the single-machine inertia response model.

3. The method according to claim 2, wherein The inter-machine oscillation model of the frequency response model is: where p1 is the steady-state part parameter corresponding to the two-part oscillation, p2, p3, p4, and p5 are all the corresponding parameters of the single-machine inertia response model, and p6, p7, p8, and p9 are all the corresponding parameters of the inter-machine oscillation model.

4. The method according to claim 1, wherein The obtaining the frequency change rate of the system at the moment of disturbance occurrence in the power system according to the frequency curve includes: Identify the frequency component of the single-machine response; Use the frequency component of the single-machine response to identify the frequency component of the inter-machine oscillation, so as to obtain the final frequency result by combining the frequency component of the single-machine response and the frequency component of the inter-machine oscillation; Obtain the frequency change rate based on the frequency curve and the final frequency result.

5. An off-line inertia identification device for a power system based on a frequency response model, characterized in that, Including: An acquisition module for obtaining the frequency response curve of the power system; An identification module for identifying the frequency curve by using the pre-constructed frequency response model and the frequency response curve; A calculation module for obtaining the frequency change rate of the system at the moment of disturbance occurrence in the power system according to the frequency curve, so as to calculate the off-line inertia of the power system.

6. The device according to claim 5, characterized in that The single-machine frequency response identification model of the frequency response model is: where p1 is the steady-state part parameter corresponding to the two-part oscillation, and p2, p3, p4, and p5 are all the corresponding parameters of the single-machine inertia response model.

7. The device according to claim 6, characterized in that, The inter-machine oscillation model of the frequency response model is: where p1 is the steady-state part parameter corresponding to the two-part oscillation, p2, p3, p4, and p5 are all the corresponding parameters of the single-machine inertia response model, and p6, p7, p8, and p9 are all the corresponding parameters of the inter-machine oscillation model.

8. An electronic device, characterized in that, Including: A memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor executes the program to implement the method for identifying the off-line inertia of a power system based on a frequency response model according to any one of claims 1-4.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to be used for implementing the method for identifying the off-line inertia of a power system based on a frequency response model according to any one of claims 1-4.

10. A computer program product, comprising a computer program, characterized in that, The computer program is executed to be used for implementing the method for identifying the off-line inertia of a power system based on a frequency response model according to any one of claims 1-4.

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