A virtual inertia configuration method considering frequency distribution characteristics and a related device

Abstract

The application discloses a virtual inertia configuration method considering frequency distribution characteristics and related devices, according to the frequency response curve of each frequency observation node under the historical power disturbance of the researched power system, the frequency change rate and the maximum frequency deviation of each node are calculated as the frequency distribution characteristic quantitative index; according to the frequency distribution characteristic quantitative index, and combining the power system frequency stability criterion, the area with lower internal frequency stability of the power system is obtained; respectively taking the frequency change rate and the maximum frequency deviation as the constraint, the equivalent model method is adopted, and the inertia demand of the researched power system is obtained by using the frequency response model; under the premise of meeting the inertia demand of the researched power system, the virtual inertia resource is preferentially configured for the area with lower internal frequency stability of the system. The method fully considers the frequency distribution difference of different areas while meeting the system frequency stability, preferentially configures the area with low frequency stability, and maximizes the frequency support ability of new energy.

Description

Technical Field

[0001] This invention relates to the field of power system technology, and in particular to a virtual inertia configuration method and related apparatus that takes into account frequency distribution characteristics. Background Technology

[0002] With the iterative upgrading of new energy power generation technologies such as photovoltaics and wind power, my country's energy structure is gradually transforming towards low-carbon and high-proportion new energy sources. The large-scale integration of new energy units will lead to an increase in the number of power electronic components in the system. Compared with conventional thermal power units, this will not only result in insufficient inertia and uneven spatial distribution within the power system, but also cause the power system to exhibit more obvious spatiotemporal frequency distribution characteristics in different regions. The frequency response processes of different nodes at different locations within the power system vary greatly over time, which is particularly evident in areas where new energy sources converge, and has an adverse impact on the frequency stability of the power system.

[0003] With the increasing proportion of renewable energy units, virtual synchronous machine technology has been widely used to ensure the safe and stable operation of the power system. However, in the research on virtual inertia deployment for renewable energy power plants, existing technologies usually only consider whether the overall inertia level within the system can support the stability of the system's inertial center frequency, without considering the frequency distribution characteristics of different regions within the system when disturbances occur. Summary of the Invention

[0004] The purpose of this invention is to provide a virtual inertia configuration method and related apparatus that considers frequency distribution characteristics. This method fully considers the frequency distribution differences in different regions while ensuring system frequency stability, prioritizes the configuration of regions with low frequency stability, and maximizes the frequency support capability of new energy sources.

[0005] The objective of this invention is achieved through the following technical solution:

[0006] A method for configuring virtual inertia that considers frequency distribution characteristics, the method comprising:

[0007] Based on the frequency response curves of each frequency observation node under the historical power disturbance of the power system under the study, the frequency change rate and maximum frequency deviation of each node are calculated, and the frequency change rate and maximum frequency deviation are used as quantitative indicators of frequency distribution characteristics.

[0008] Based on the aforementioned frequency distribution characteristic quantification index and combined with the power system frequency stability criterion, the region with low frequency stability within the power system is obtained.

[0009] Using the rate of change of frequency and the maximum frequency deviation as constraints, the inertia requirement of the power system under study is obtained by using the equivalent model method and the frequency response model.

[0010] While meeting the inertia requirements of the power system under study, virtual inertia resources are configured for regions with low frequency stability within the power system.

[0011] A virtual inertia configuration device considering frequency distribution characteristics, the device comprising:

[0012] The frequency distribution characteristic quantification index acquisition unit is used to calculate the frequency change rate and maximum frequency deviation of each node based on the frequency response curve of each frequency observation node under the historical power disturbance of the power system under study, and uses the frequency change rate and maximum frequency deviation as the frequency distribution characteristic quantification index.

[0013] The low frequency stability region acquisition unit is used to obtain the region with low frequency stability within the power system based on the frequency distribution characteristic quantification index and in combination with the power system frequency stability criterion.

[0014] The power system inertia demand acquisition unit is used to obtain the inertia demand of the power system under study by using the equivalent model method and frequency response model, with the frequency change rate and maximum frequency deviation as constraints respectively.

[0015] The virtual inertia resource allocation unit is used to allocate virtual inertia resources for areas with low frequency stability within the power system, while meeting the inertia requirements of the power system under study.

[0016] An electronic device includes a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to execute any of the aforementioned virtual inertia configuration methods considering frequency distribution characteristics.

[0017] A computer storage medium storing a plurality of instructions adapted for loading and execution by a processor of any one of the aforementioned virtual inertia configuration methods considering frequency distribution characteristics.

[0018] As can be seen from the technical solution provided by the present invention, the above method can calculate the frequency distribution characteristic quantitative index based on the frequency response curve under historical power disturbance, divide the frequency stable region based on the index, and then obtain the inertia requirement of the power system under study, and configure the virtual inertia of different regions, thereby maximizing the frequency support capability of new energy sources. This is of great significance for ensuring the safe and stable operation of the power system and improving the acceptance capability of new energy sources. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A schematic flowchart of a virtual inertia configuration method considering frequency distribution characteristics provided in an embodiment of the present invention;

[0021] Figure 2 This is a schematic diagram of the system frequency response model built according to an embodiment of the present invention;

[0022] Figure 3 This is a wiring diagram of the IEEE 10 machine 39-node system including the fan as described in an embodiment of the present invention;

[0023] Figure 4 The frequency response curves of each observation node described in the embodiments of the present invention;

[0024] Figure 5 This is a schematic diagram illustrating the quantitative indicators of the distribution characteristics of each observation node as described in an embodiment of the present invention;

[0025] Figure 6 This is a schematic diagram of the quantitative indicators of the distribution characteristics of each observation node after adjusting the inertia level according to an embodiment of the present invention. Detailed Implementation

[0026] 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, and not all embodiments, and do not constitute a limitation of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present invention.

[0027] like Figure 1 The diagram shown is a schematic flowchart of a virtual inertia configuration method considering frequency distribution characteristics provided in an embodiment of the present invention. The method includes:

[0028] Step 1: Based on the frequency response curves of each frequency observation node under the historical power disturbance of the power system under study, calculate the frequency change rate and maximum frequency deviation of each node, and use the frequency change rate and maximum frequency deviation as quantitative indicators of frequency distribution characteristics.

[0029] In this step, the frequency response curves of each frequency observation node under historical power disturbances of the power system under study are first obtained. Based on the frequency response curves, the quantitative index of frequency distribution characteristics is obtained, where the maximum frequency deviation Δf is the most significant indicator.max It can be obtained from the following formula:

[0030] Δf max =f N -f min (1)

[0031] In the formula: f N For the steady-state frequency, we take 50Hz; f min This is the minimum value during the frequency response process;

[0032] The rate of change of frequency, RoCoF, is the maximum value of RoCoF during the frequency dynamic response process. max It is obtained by using the sliding window method according to the following formula:

[0033]

[0034] In the formula: df / dt(i+1) is the rate of change of frequency at the sampling time corresponding to the (i+1)th sampling point of the frequency time series; f(i) is the frequency value at the i-th sampling point of the frequency time series; Δt is the sliding window time.

[0035] Step 2: Based on the frequency distribution characteristic quantification index and combined with the power system frequency stability criterion, obtain the region with low frequency stability within the power system.

[0036] In this step, the frequency change rate RoCoF is required to be within a value that will not cause anti-islanding protection to operate. Generally, the RoCoF of the power system's center of inertia is considered to be within this range. max It should be less than 0.5 Hz / s; for the maximum frequency deviation Δf max It is required that it should not fall below a certain specific value, thereby causing the new energy units to disconnect from the grid and triggering low-frequency load shedding actions;

[0037] Based on the frequency distribution characteristics quantification index, the frequency stability of each region within the power system is determined, and the region with low frequency stability within the studied power system is obtained. The specific method is as follows:

[0038] By determining the frequency change rate RoCoF and the maximum frequency deviation Δf at each node max RoCoF deviates from the center of inertia of the power system sys max and Δf sys max The degree of deviation of the i-th observation node is expressed as:

[0039]

[0040] In the formula, RoCoF max (i) represents the rate of change of the frequency at the i-th observation node; RoCoFsysmax Δf is the rate of change of frequency at the center of inertia of the power system. max (i) represents the maximum frequency deviation of the i-th observation node; Δf sysmax This represents the maximum frequency deviation of the power system's center of inertia.

[0041] According to equation (3), the region where the node with a large degree of deviation and the absolute value of the frequency distribution characteristic quantitative index is larger than the absolute value of the power system inertia center index is determined to be a region with low frequency stability inside the power system.

[0042] Step 3: Using the rate of change of frequency and the maximum frequency deviation as constraints, respectively, the inertia requirement of the power system under study is obtained by using the equivalent model method and the frequency response model.

[0043] In this step, the rate of change of frequency RoCoF occurs at the initial moment of the disturbance and is related to the unbalanced power and inertia level. It is usually required to be no greater than a certain fixed value, and the relationship between the three is as follows:

[0044] 2H*RoCoF=ΔP L (4)

[0045] In the formula: H is the equivalent inertial time constant; ΔP L This is due to a power deficit.

[0046] Maximum frequency deviation Δf max Typically, a few seconds after a disturbance, the system frequency drops to a fixed value, triggering the first stage of low-frequency load shedding. An equivalent model method is used to construct the system frequency response model, such as... Figure 2 The diagram shown is a schematic of the system frequency response model constructed according to an embodiment of the present invention. Figure 2 It can be seen that when the system experiences a power deficit of ΔP L After the perturbation, the relationship between the three is as follows:

[0047]

[0048] In the formula: Δf is the frequency deviation; s is the Laplace operator; F HP T is the equivalent high-pressure turbine power coefficient of the system; RH R is the system equivalent speed governor time constant; R is the system equivalent static droop coefficient; D is the load damping coefficient.

[0049] Based on equations 4 and 5, the minimum inertia requirement H under the RoCoF constraint of the rate of frequency change can be obtained. min1 and the maximum frequency deviation Δf max Minimum inertia requirement H under constraints min2 And finally, the minimum inertia requirement H of the power system under study is obtained. min , represented as:

[0050] H min =max{H min1 H min2} (6).

[0051] Step 4: Under the premise of meeting the inertia requirements of the power system under study, configure virtual inertia resources for the regions with low frequency stability within the power system.

[0052] In this step, based on the regions with low frequency stability within the power system obtained in step 2 and the inertia requirements of the power system under study obtained in step 3, while keeping the overall inertia level of the power system above a certain value, considering the distribution characteristics of the frequency response due to the uneven distribution of inertia level and the topological factors within the system, virtual inertia resources are prioritized for regions that exceed the frequency stability criterion limit or regions with low frequency stability within the system.

[0053] Among them, the frequency stability criterion exceeding the limit refers to the maximum frequency change rate RoCoF. max The absolute value is greater than 0.5 Hz / s and the maximum frequency deviation Δf max Exceeding the low-frequency load reduction threshold.

[0054] Based on the above method, embodiments of the present invention also provide a virtual inertia configuration device that considers frequency distribution characteristics, the device comprising:

[0055] The frequency distribution characteristic quantification index acquisition unit is used to calculate the frequency change rate and maximum frequency deviation of each node as a frequency distribution characteristic quantification index based on the frequency response curves of each frequency observation node under the historical power disturbance of the power system under study.

[0056] The low frequency stability region acquisition unit is used to obtain the region with low frequency stability within the power system based on the frequency distribution characteristic quantification index and in combination with the power system frequency stability criterion.

[0057] The power system inertia demand acquisition unit is used to obtain the inertia demand of the power system under study by using the equivalent model method and frequency response model, with the frequency change rate and maximum frequency deviation as constraints respectively.

[0058] The virtual inertia resource allocation unit is used to prioritize the allocation of virtual inertia resources for areas with low frequency stability within the power system, while meeting the inertia requirements of the power system under study.

[0059] The specific implementation process of each unit of the above-mentioned device is described in the above method embodiments.

[0060] The method described in this invention will be illustrated below with a specific example. This embodiment uses an IEEE 10-machine 39-node system with a wind turbine to demonstrate the effectiveness of the invention. Figure 3 The diagram shown is a wiring diagram of an IEEE 10-unit 39-node system with wind turbines according to an embodiment of the present invention. The system includes ten units, of which seven are synchronous units, three are wind farm equivalent aggregation units, the balancing node is generator node 31, the system's renewable energy penetration rate is 28%, and the disturbance is set as a sudden load increase.

[0061] by Figure 3 The nodes marked in the text are frequency observation nodes, such as... Figure 4 The figure shows the frequency response curves of each observation node. Figure 4 The frequency response curves shown can be used to quantify the distribution characteristics of each observation node, such as... Figure 5 The diagram shows a quantitative index of the distribution characteristics of each observation node according to an embodiment of the present invention.

[0062] By comparing and analyzing the distribution characteristics and quantitative indicators to rank frequency stability, in the example system, when a disturbance occurs, the area where observation node 5 is located is a region with low frequency stability, which is the area where new energy units converge. Following the method described in this example, the inertia level of the low-frequency stability region of observation node 5 is prioritized, such as... Figure 6 The diagram shown is a quantitative index of the distribution characteristics of each observation node after adjusting the inertia level according to an embodiment of the present invention. Figure 6 As can be seen from this, the virtual inertia configuration method considering the distribution characteristics proposed in this invention can effectively improve the frequency stability criterion and ensure the frequency stability of the power system.

[0063] It is worth noting that the contents not described in detail in the embodiments of the present invention belong to the prior art known to those skilled in the art.

[0064] This application provides an electronic device, which includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it performs the following steps: based on the frequency response curves of each frequency observation node under historical power disturbances of the power system under study, it calculates the frequency change rate and maximum frequency deviation of each node as quantitative indicators of frequency distribution characteristics; based on the quantitative indicators of frequency distribution characteristics and combined with the power system frequency stability criterion, it obtains the region with low frequency stability within the power system; using the frequency change rate and maximum frequency deviation as constraints, it uses the equivalent model method and frequency response model to obtain the inertia requirement of the power system under study; under the premise of meeting the inertia requirement of the power system under study, it prioritizes the allocation of virtual inertia resources for the region with low frequency stability within the system.

[0065] Furthermore, those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware, and the corresponding program can be stored in a computer storage medium, such as a read-only memory, a disk, or an optical disk.

[0066] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims. The information disclosed in the background section is intended only to enhance the understanding of the overall background technology of the present invention and should not be construed as an admission or implication in any way that such information constitutes prior art known to those skilled in the art.

Claims

1. A method for configuring virtual inertia considering frequency distribution characteristics, characterized in that, The method includes: Based on the frequency response curves of each frequency observation node under the historical power disturbance of the power system under the study, the frequency change rate and maximum frequency deviation of each node are calculated, and the frequency change rate and maximum frequency deviation are used as quantitative indicators of frequency distribution characteristics. Based on the aforementioned frequency distribution characteristic quantification index and combined with the power system frequency stability criterion, the region with low frequency stability within the power system is obtained. Using the rate of frequency change and maximum frequency deviation as constraints, the inertia demand of the power system under study is obtained through the equivalent model method and frequency response model using the frequency response model. The specific process is as follows: The rate of change of frequency, RoCoF, occurs at the initial moment of the disturbance and is related to the unbalanced power and inertia level. The relationship among the three is as follows: （4） In the formula: H is the equivalent inertial time constant; ∆P L This is due to a power deficit. Maximum frequency deviation ∆f max Appearing a few seconds after the disturbance, an equivalent model method is used to build the system frequency response model. When the system experiences a power deficit of ∆P... L After the perturbation, the relationship between the three is as follows: （5） In the formula: is the frequency deviation; s is the Laplace operator; F HP T is the equivalent high-pressure turbine power coefficient of the system; RH R is the system equivalent speed governor time constant; R is the system equivalent static droop coefficient; D is the load damping coefficient. The minimum inertia requirement H under the RoCoF constraint of the rate of frequency change is obtained based on equations 4 and 5. min1 and the maximum frequency deviation ∆f max Minimum inertia requirement H under constraints min2 And obtain the minimum inertia requirement of the power system under study. , represented as: （6）； Under the premise of meeting the inertia requirements of the power system under study, virtual inertia resources are configured for regions with low frequency stability within the power system. Specifically, the process of obtaining the region with low frequency stability within the power system based on the frequency distribution characteristic quantification index and in conjunction with the power system frequency stability criterion is as follows: By determining the frequency change rate RoCoF and the maximum frequency deviation ∆f at each node max RoCoF deviates from the center of inertia of the power system sys max and ∆f sys max The degree of deviation of the i-th observation node is expressed as: （3） In the formula, Let i be the rate of change of the frequency at the i-th observation node; The rate of change of frequency at the center of inertia of the power system; The maximum frequency deviation of the i-th observation node; This represents the maximum frequency deviation of the power system's center of inertia. According to equation (3), the region where the deviation is greater than the set threshold and the absolute value of the frequency distribution characteristic quantitative index is greater than the absolute value of the power system inertia center index is determined as the region with low frequency stability inside the power system. Among them, deviation includes and ; Rate of change of frequency RoCoF and maximum frequency deviation ∆f max As a quantitative indicator of frequency distribution characteristics.

2. The virtual inertia configuration method considering frequency distribution characteristics according to claim 1, characterized in that, The process of calculating the frequency change rate and maximum frequency deviation of each node based on the frequency response curves of each frequency observation node under historical power disturbances of the studied power system, and using the frequency change rate and maximum frequency deviation as quantitative indicators of frequency distribution characteristics, is specifically as follows: The frequency response curves of each frequency observation node under historical power disturbances of the studied power system are obtained. Based on the frequency response curves, the quantitative index of frequency distribution characteristics is obtained, including the maximum frequency deviation ∆f. max It can be obtained from the following formula: （1） In the formula: f N The steady-state frequency; f min This is the minimum value during the frequency response process; The rate of change of frequency, RoCoF, is the maximum value of RoCoF during the frequency dynamic response process. max It is obtained by using the sliding window method according to the following formula: （2） In the formula: df / dt(i+1) is the rate of change of frequency at the sampling time corresponding to the (i+1)th sampling point of the frequency time series; f(i) is the frequency value at the i-th sampling point of the frequency time series; Δt is the sliding window time.

3. The virtual inertia configuration method considering frequency distribution characteristics according to claim 1, characterized in that, The process of configuring virtual inertia resources for regions with low frequency stability within a power system, while meeting the inertia requirements of the power system under study, is as follows: Based on the regions with low frequency stability within the power system and the inertia requirements of the power system under study, and considering the distribution characteristics of frequency response due to uneven horizontal distribution of inertia and topological factors within the power system, virtual inertia resources are configured for regions where the frequency stability criterion exceeds the limit or regions with low frequency stability within the power system. Among them, the frequency stability criterion exceeding the limit refers to the maximum frequency change rate RoCoF. max The absolute value is greater than 0.5 Hz / s and the maximum frequency deviation ∆f max Exceeding the low-frequency load reduction threshold.

4. A virtual inertia configuration device considering frequency distribution characteristics, characterized in that, The device includes: The frequency distribution characteristic quantification index acquisition unit is used to calculate the frequency change rate and maximum frequency deviation of each node based on the frequency response curve of each frequency observation node under the historical power disturbance of the power system under study, and uses the frequency change rate and maximum frequency deviation as the frequency distribution characteristic quantification index. The low frequency stability region acquisition unit is used to obtain the region with low frequency stability within the power system based on the frequency distribution characteristic quantification index and in combination with the power system frequency stability criterion. The implementation process of the low frequency stability region acquisition unit is as follows: By determining the frequency change rate RoCoF and the maximum frequency deviation ∆f at each node max RoCoF deviates from the center of inertia of the power system sys max and ∆f sys max The degree of deviation of the i-th observation node is expressed as: （3） In the formula, Let i be the rate of change of the frequency at the i-th observation node; The rate of change of frequency at the center of inertia of the power system; The maximum frequency deviation of the i-th observation node; This represents the maximum frequency deviation of the power system's center of inertia. According to equation (3), the region where the deviation is greater than the set threshold and the absolute value of the frequency distribution characteristic quantitative index is greater than the absolute value of the power system inertia center index is determined as the region with low frequency stability inside the power system. Among them, deviation includes and ; Rate of change of frequency RoCoF and maximum frequency deviation ∆f max As a quantitative indicator of frequency distribution characteristics; The power system inertia demand acquisition unit is used to obtain the inertia demand of the power system under study by employing the equivalent model method and utilizing the frequency response model, with frequency change rate and maximum frequency deviation as constraints respectively; the specific process is as follows: The rate of change of frequency, RoCoF, occurs at the initial moment of the disturbance and is related to the unbalanced power and inertia level. The relationship among the three is as follows: （4） In the formula: H is the equivalent inertial time constant; ∆P L This is due to a power deficit. Maximum frequency deviation ∆f max Appearing a few seconds after the disturbance, an equivalent model method is used to build the system frequency response model. When the system experiences a power deficit of ∆P... L After the perturbation, the relationship between the three is as follows: （5） In the formula: is the frequency deviation; s is the Laplace operator; F HP T is the equivalent high-pressure turbine power coefficient of the system; RH R is the system equivalent speed governor time constant; R is the system equivalent static droop coefficient; D is the load damping coefficient. The minimum inertia requirement H under the RoCoF constraint of the rate of frequency change is obtained based on equations 4 and 5. min1 and the maximum frequency deviation ∆f max Minimum inertia requirement H under constraints min2 And obtain the minimum inertia requirement of the power system under study. , represented as: （6）； The virtual inertia resource allocation unit is used to allocate virtual inertia resources for areas with low frequency stability within the power system, while meeting the inertia requirements of the power system under study.

5. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to run the computer program to perform the virtual inertia configuration method considering frequency distribution characteristics as described in any one of claims 1 to 3.

6. A computer storage medium, characterized in that, The computer storage medium stores multiple instructions, which are adapted to be loaded by a processor and executed by the virtual inertia configuration method considering frequency distribution characteristics as described in any one of claims 1 to 3.

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