New energy inertia stability evaluation method with strong robustness and consideration of multiple targets

Abstract

The invention discloses a strong-robustness new energy inertia stability evaluation method considering multiple targets. The method comprises the steps of setting a plurality of first-level indexes for evaluating stability and a plurality of second-level indexes included in each first-level index; normalizing each data in the data sample; wherein the data sample comprises data of a plurality of operation schemes of the new energy power grid, and the data of each operation scheme comprises all secondary indexes; determining a weight coefficient of each secondary index; and based on the normalized data of the data sample and the weight coefficient of each secondary index, determining a comprehensive score of the stability of each operation scheme. The comprehensive score obtained by using the method considers the multi-target demand, and the operation scheme of the new energy power grid considering the multi-target demand can be selected by using the method.

Description

Technical Field

[0001] The present application relates to the technical field of stability evaluation, and in particular to a new energy inertia stability evaluation method with strong robustness and multi-objective considerations. Background Art

[0002] As new energy generation technologies continue to mature and costs continue to fall, new energy generation facilities such as wind farms and photovoltaic power stations continue to emerge, gradually changing the traditional electricity production pattern dominated by fossil fuels. Although new energy generation technologies such as wind power and photovoltaics have the advantages of being clean and renewable, their inherent intermittent and volatile characteristics also bring considerable challenges to the stable operation of the power system. Compared with traditional thermal power units, the output power of new energy generation is often difficult to predict and control, which directly leads to a significant reduction in the system inertia level.

[0003] To solve the problem of insufficient inertia caused by renewable energy power generation, virtual inertia technology came into being. Virtual inertia simulates the inertia characteristics of traditional synchronous generators through power electronics in energy storage systems or renewable energy power generation equipment, thereby improving the frequency stability of the system. However, existing inertia control methods often only focus on a single goal, such as frequency response time or smoothness of power output, ignoring the multi-objective optimization needs in the overall operation of the system. Summary of the invention

[0004] The embodiment of the present application solves the technical problem that the inertia control method of the new energy power grid in the prior art is difficult to integrate the multi-objective requirements of the system by providing a highly robust new energy inertia stability evaluation method that takes multiple objectives into consideration.

[0005] In the first aspect, an embodiment of the present application provides a new energy inertia stability evaluation method with strong robustness and considering multiple objectives, the method comprising: setting multiple primary indicators for evaluating stability and multiple secondary indicators included in each of the primary indicators; normalizing each data in a data sample; wherein the data sample comprises data of multiple operation schemes of the new energy power grid, and the data of each of the operation schemes comprises all of the secondary indicators; determining a weight coefficient of each of the secondary indicators; and determining a comprehensive score for the stability of each of the operation schemes based on the normalized data of the data sample and the weight coefficient of each of the secondary indicators.

[0006] In combination with the first aspect, in a possible implementation manner, before determining the weight coefficient of each of the secondary indicators, the method further includes: completing the missing data in the data sample.

[0007] In combination with the first aspect, in a possible implementation method, the filling in the missing data in the data sample includes: setting the missing data to zero; determining a coefficient vector based on the product of a pseudo-pseudo-matrix of the first matrix and a first vector; wherein the first matrix is ​​composed of the remaining data of the data sample after removing all data of the operating scheme where the missing data is located and the corresponding secondary indicators, and the first vector is composed of all normal data in the operating scheme where the missing data is located; determining the value of the missing data based on the product of a second vector and the coefficient vector; wherein the second vector is composed of all normal data of the secondary indicators corresponding to the missing data.

[0008] In combination with the first aspect, in a possible implementation manner, normalizing each data in the data sample includes: for the data corresponding to the secondary indicator belonging to the positive indicator, normalizing by using the following formula: ; For the data corresponding to the secondary indicators that are negative indicators, the following formula is used for normalization: ; where X ij The data of the jth secondary indicator of the i-th operation plan, S ij Represents X ij After normalization, max(x j ) represents the maximum value of the j-th secondary index, min(x j ) represents the minimum value of the j-th secondary index.

[0009] In combination with the first aspect, in a possible implementation manner, determining the weight coefficient of each of the secondary indicators includes: determining the weight coefficient of each of the secondary indicators by using a CRITIC method.

[0010] In combination with the first aspect, in a possible implementation, the method further includes: determining the stability level of each of the operating schemes based on the comprehensive score and a preset stability evaluation level comparison table.

[0011] In combination with the first aspect, in a possible implementation method, the first-level indicators include frequency stability, economic cost and renewable energy utilization rate; the multiple second-level indicators of frequency stability include frequency response time, frequency regulation capability and frequency fluctuation amplitude; the multiple second-level indicators of economic cost include system construction cost, operation and maintenance cost and economic rate of return; the multiple second-level indicators of renewable energy utilization rate include renewable energy penetration rate, energy storage system utilization rate and carbon emission reduction benefits.

[0012] In the second aspect, an embodiment of the present application provides a new energy inertia stability evaluation device with strong robustness and considering multiple objectives, the device comprising: a setting module, used to set multiple primary indicators for evaluating stability and multiple secondary indicators included in each of the primary indicators; a normalization module, used to normalize each data in a data sample; wherein the data sample includes data of multiple operation schemes of the new energy power grid, and the data of each of the operation schemes includes all of the secondary indicators; a weight module, used to determine the weight coefficient of each of the secondary indicators; a scoring module, used to determine a comprehensive score for the stability of each of the operation schemes based on the normalized data of the data sample and the weight coefficient of each of the secondary indicators.

[0013] In a third aspect, an embodiment of the present application provides an electronic device comprising: one or more processors; and a memory storing computer executable instructions, wherein the computer executable instructions, when executed by the one or more processors, enable the one or more processors to execute the new energy inertia stability evaluation method with strong robustness and considering multiple objectives as described in the first aspect or any possible implementation of the first aspect.

[0014] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores computer-readable instructions, which, when executed by a computer, implement the new energy inertia stability evaluation method with strong robustness and considering multiple objectives as described in the first aspect or any possible implementation method of the first aspect.

[0015] The technical solution provided in the embodiments of the present application has at least the following technical effects: An embodiment of the present application provides a highly robust new energy inertia stability evaluation method that takes into account multiple objectives. The method sets multiple first-level indicators for evaluating stability, and each first-level indicator is subdivided into multiple second-level indicators. By weighting each second-level indicator, a comprehensive score is calculated; the comprehensive score takes into account multiple objective requirements. By using this method, an operation plan for a new energy power grid that takes into account multiple objective requirements can be selected. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments of the present application will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 A flowchart of a new energy inertia stability evaluation method with strong robustness and multi-objective considerations provided in an embodiment of the present application; Figure 2 A flowchart for completing missing data in a data sample provided in an embodiment of the present application; Figure 3 A schematic diagram of a new energy inertia stability evaluation device with strong robustness and multi-objective considerations provided in an embodiment of the present application. DETAILED DESCRIPTION

[0018] With the continuous maturity of new energy power generation technology and the continuous decline in costs, new energy power generation facilities such as wind farms and photovoltaic power stations continue to emerge. However, the intermittent and volatile nature of new energy sources such as wind power and photovoltaics poses challenges to the stability of the power system, because their output power is difficult to predict and control, resulting in a reduction in system inertia. For this reason, virtual inertia technology has emerged, using energy storage or power electronics devices to simulate the inertia of traditional generators and improve system frequency stability. However, existing inertia control methods mostly focus on a single goal and ignore the multi-objective optimization needs of the system as a whole.

[0019] In view of the above reasons, the embodiment of the present application provides a new energy inertia stability evaluation method with strong robustness and multi-objective considerations. The technical scheme in the embodiment of the present application will be clearly and completely described in combination with the drawings in the embodiment of the present application. Obviously, the described embodiment is a part of the embodiment of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0020] In the embodiments of the present application, the terms "first", "second", and "third" are used for descriptive purposes only and should not be understood to imply relative importance or the number of technical features indicated. In the description of the embodiments of the present application, unless otherwise specified, the meaning of "multiple" is two or more.

[0021] The embodiment of the present application provides a new energy inertia stability evaluation method with strong robustness and considering multiple objectives. Figure 1 As shown, the method includes steps S101 to S104.

[0022] S101: Setting a plurality of primary indicators for evaluating stability and a plurality of secondary indicators included in each primary indicator.

[0023] By setting multiple first-level indicators and multiple second-level indicators included in each first-level indicator through step S101, an evaluation system for the stability of the new energy power grid is formed. Since multiple first-level indicators cover multiple target requirements, the final evaluation result of the method can take multiple target requirements into consideration.

[0024] Exemplarily, multiple first-level indicators for evaluating stability are set as: frequency stability, economic cost and renewable energy utilization rate; multiple second-level indicators for frequency stability are set as: frequency response time, frequency regulation capability and frequency fluctuation amplitude; multiple second-level indicators for economic cost are set as: system construction cost, operation and maintenance cost and economic rate of return; multiple second-level indicators for renewable energy utilization rate are set as: renewable energy penetration rate, energy storage system utilization rate and carbon emission reduction benefit.

[0025] S102: Normalize each data in the data sample, wherein the data sample includes data of multiple operation plans of the new energy power grid, and the data of each operation plan includes all secondary indicators.

[0026] Since the units of the secondary indicators may be different, step S102 normalizes each data in the data sample, which can eliminate the influence of the dimension of each secondary indicator on the evaluation result.

[0027] S103: Determine the weight coefficient of each secondary indicator. After executing step S103, a vector of weight coefficients covering each secondary indicator is obtained. Exemplarily, the vector of weight coefficients is determined as follows: .

[0028] In the embodiment of the present application, step S103 includes: determining the weight coefficient of each secondary indicator through the CRITIC (Criteria Importance Through Intercriteria Correlation) method.

[0029] In other embodiments of the present application, step S103 may also determine the weight coefficient of each secondary indicator by principal component analysis, entropy method, or the like.

[0030] S104: Based on the normalized data of the data sample and the weight coefficient of each secondary indicator, determine the comprehensive score of the stability of each operation scheme. Specifically, the comprehensive score is the sum of the scores of each primary indicator, and the score of each primary indicator is the sum of the products of the corresponding values ​​of multiple secondary indicators and the corresponding weight coefficients.

[0031] For example, step S101 is provided with three first-level indicators, namely, frequency stability G1, economic cost G2, and renewable energy utilization rate G3; frequency stability G1 includes three second-level indicators, namely, frequency response time F1, frequency regulation capability F2, and frequency fluctuation amplitude F3; economic cost G2 includes three second-level indicators, namely, system construction cost C1, operation and maintenance cost C2, and economic rate of return C3; renewable energy utilization rate G3 includes three second-level indicators, namely, renewable energy penetration rate R1, energy storage system utilization rate R2, and carbon emission reduction benefit R3; the weight coefficients corresponding to frequency response time F1, frequency regulation capability F2, frequency fluctuation amplitude F3, system construction cost C1, operation and maintenance cost C2, economic rate of return C3, renewable energy penetration rate R1, energy storage system utilization rate R2, and carbon emission reduction benefit R3 are ; Based on the above multiple first-level indicators and multiple second-level indicators, the comprehensive score S is calculated by the following formula:

[0032] The above method in the embodiment of the present application sets up multiple first-level indicators for evaluating stability, and the multiple first-level indicators cover multiple target requirements, and each first-level indicator is subdivided into multiple second-level indicators. By weighting each second-level indicator, a comprehensive score is calculated; the comprehensive score takes into account multiple target requirements. By using this method, an operation plan for a new energy power grid that takes into account multiple target requirements can be selected.

[0033] The operating environment of the new energy grid is complex and changeable, and some data acquisition equipment may fail, resulting in missing data. In an embodiment of the present application, before step S103, the method also includes: completing the missing data in the data sample. After executing step S103, the comprehensive score obtained by the method can be made more accurate, reducing the impact of missing data on the overall evaluation quality and reducing the dependence of stability evaluation on comprehensive and complete data.

[0034] like Figure 2 As shown, in the embodiment of the present application, the process of completing missing data in the data sample includes steps S201 to S203.

[0035] S201, setting missing data to zero. In step S201, zero is used to temporarily replace missing data, so that step S103 can normalize all data in the data sample.

[0036] S202, determine the coefficient vector based on the product of the pseudo-quasi-matrix of the first matrix and the first vector. The first matrix is ​​composed of the remaining data of the data sample after removing all the data of the operation scheme where the missing data is located and the corresponding secondary indicators, and the first vector is composed of all the normal data in the operation scheme where the missing data is located; the specific calculation formula of the coefficient vector is as follows:

[0037] in, is the coefficient vector, is the first matrix, is the first vector, For missing data, To find the function of the pseudo-matrix.

[0038] S203, determine the value of the missing data based on the product of the second vector and the coefficient vector. The second vector is composed of all normal data of the secondary indicators corresponding to the missing data; the specific calculation formula is as follows: .

[0039] Each data in the normalized data sample includes: For the data corresponding to the secondary indicators belonging to the positive indicators, the following formula is used for normalization: ; For the data corresponding to the secondary indicators that are negative indicators, the following formula is used for normalization: ;in, Represents the data of the jth secondary indicator of the i-th operation plan, After normalization, represents the maximum value of the j-th secondary index, Indicates the minimum value of the j-th secondary index.

[0040] The method provided in the embodiment of the present application further includes: determining the stability level of each operation scheme based on the comprehensive score and the preset stability evaluation level comparison table. For example, Table 1 shows the preset stability evaluation level comparison table.

[0041] Table 1 Rating Comprehensive score range Level Description Level I 90%≤S≤100% Excellent stability Level II 75%≤S<90% Good stability Grade III 60%≤S<75% Average stability Level IV <60% Poor stability A complete example is given below to illustrate the above-mentioned strong robustness and multi-objective new energy inertia stability evaluation method.

[0042] The data samples of the new energy grid are shown in Table 2, where the data in the operation schemes S1 to S2 are complete. x The secondary indicator “frequency adjustment ability” has missing data, and the missing data are set to zero.

[0043] Table 2 Based on Table 2, when using the above method for stability evaluation, first, frequency stability G1, economic cost G2 and renewable energy utilization rate G3 are set as primary indicators; frequency stability G1 is set to include three secondary indicators, namely frequency response time F1, frequency regulation capability F2 and frequency fluctuation amplitude F3; economic cost G2 is set to include three secondary indicators, namely system construction cost C1, operation and maintenance cost C2 and economic rate of return C3; renewable energy utilization rate G3 is set to include three secondary indicators, namely renewable energy penetration rate R1, energy storage system utilization rate R2 and carbon emission reduction benefit R3.

[0044] Secondly, each data in the data samples shown in Table 2 is normalized to obtain Table 3.

[0045] Table 3

[0046] Then, based on the data in Table 3, the coefficient vector is solved by the following formula: ;in, is a function for solving pseudo-matrix.

[0047] And, missing data is solved by the following formula Where b=2; .

[0048] The above calculation result is 0.920, the actual missing data is 0.932, and the relative error is only 1.3%, so the completed missing data is relatively close to the real data. Through the above method, even in the case of missing data, the above method can still be used to evaluate the stability of the new energy power grid.

[0049] In addition, the CRTITIC method is used to calculate the weight coefficient of each secondary indicator, and the vector of the secondary indicator weight is as follows: .

[0050] Finally, the score of each first-level indicator is calculated by the following formula: The overall score of each running plan .

[0051] Taking the running scheme S5 as an example, the calculation results of the comprehensive score are shown in Table 4.

[0052] Table 4

[0053] From Table 4, we can see that the comprehensive evaluation score of operation plan S5 is 0.646, and from Table 1, we can conclude that the stability evaluation level of the new energy grid of this operation plan is level III, and the effect is "general stability". Figure 3As shown, the embodiment of the present application also provides a new energy inertia stability evaluation device 300 with strong robustness and considering multiple objectives. The device includes a setting module 301, a normalization module 302, a weight module 303 and a scoring module 304.

[0054] The setting module 301 is used to set multiple primary indicators for evaluating stability and multiple secondary indicators included in each primary indicator. The normalization module 302 is used to normalize each data in the data sample; wherein the data sample includes data of multiple operation plans of the new energy power grid, and the data of each operation plan includes all secondary indicators. The weight module 303 is used to determine the weight coefficient of each secondary indicator. The scoring module 304 is used to determine the comprehensive score of the stability of each operation plan based on the normalized data of the data sample and the weight coefficient of each secondary indicator.

[0055] The highly robust new energy inertia stability evaluation device taking multiple objectives into consideration provided in the embodiment of the present application also includes a completion module, which is used to complete the missing data in the data sample.

[0056] The completion module is specifically used to: set the missing data to zero; determine the coefficient vector based on the product of the pseudo-pseudo-matrix of the first matrix and the first vector; wherein the first matrix is ​​composed of the remaining data of the data sample after removing all the data of the operating scheme where the missing data is located and the corresponding secondary indicators, and the first vector is composed of all the normal data in the operating scheme where the missing data is located; determine the value of the missing data based on the product of the second vector and the coefficient vector; wherein the second vector is composed of all the normal data of the secondary indicators corresponding to the missing data.

[0057] The normalization module 302 is specifically used to normalize the data corresponding to the secondary indicators belonging to the positive indicators using the following formula: ; For the data corresponding to the secondary indicators that are negative indicators, the following formula is used for normalization: ;in, Represents the data of the jth secondary indicator of the i-th operation plan, express After normalization, represents the maximum value of the j-th secondary index, Indicates the minimum value of the j-th secondary index.

[0058] The weight module 303 is specifically used to determine the weight coefficient of each secondary indicator through the CRITIC method.

[0059] The highly robust new energy inertia stability evaluation device taking into account multiple objectives provided in the embodiment of the present application also includes a rating module, which is used to determine the stability level of each operating scheme based on a comprehensive score and a preset stability evaluation level comparison table.

[0060] Specifically, the first-level indicators include frequency stability, economic cost and renewable energy utilization rate; multiple second-level indicators of frequency stability include frequency response time, frequency regulation capability and frequency fluctuation amplitude; multiple second-level indicators of economic cost include system construction cost, operation and maintenance cost and economic rate of return; multiple second-level indicators of renewable energy utilization rate include renewable energy penetration rate, energy storage system utilization rate and carbon emission reduction benefits.

[0061] The system or module described in the above embodiment can be implemented by a computer chip or entity, or by a product with a certain function. For the convenience of description, the above system is described by dividing it into various modules according to its function. When implementing the embodiment of the present application, the functions of each module can be implemented in the same or more software and / or hardware. Of course, the module that implements a certain function can also be implemented by combining multiple sub-modules or sub-units.

[0062] An embodiment of the present application provides an electronic device, which includes: one or more processors; and a memory storing computer-executable instructions, wherein when the computer-executable instructions are executed by the one or more processors, the one or more processors execute the above-mentioned strong robustness and multi-objective new energy inertia stability evaluation method.

[0063] An embodiment of the present application provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by a computer, the above-mentioned strong robustness and multi-objective new energy inertia stability evaluation method is implemented.

[0064] The above-mentioned storage media include but are not limited to random access memory (RAM), read-only memory (ROM), cache, hard disk drive (HDD) or memory card (Memory Card).

[0065] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other. Each embodiment focuses on the differences from other embodiments.

[0066] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit the present application. Although the present application has been described in detail with reference to the aforementioned embodiments, a person of ordinary skill in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some or all of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the present application.

Claims

1. A robust new energy inertia stability evaluation method considering multiple objectives, characterized in that: include: Setting a plurality of primary indicators for evaluating stability and a plurality of secondary indicators included in each of the primary indicators; Normalize each data in the data sample; wherein the data sample includes data of multiple operation schemes of the new energy power grid, and the data of each operation scheme includes all the secondary indicators; Determining the weight coefficient of each of the secondary indicators; Based on the normalized data of the data samples and the weight coefficient of each of the secondary indicators, a comprehensive score for the stability of each of the operating schemes is determined.

2. The method according to claim 1, characterized in that Before determining the weight coefficient of each of the secondary indicators, the method further includes: Complete the missing data in the data sample.

3. The method according to claim 2, characterized in that The method of completing the missing data in the data sample comprises: setting said missing data to zero; Determine a coefficient vector based on the product of a pseudo-pseudo-matrix of the first matrix and a first vector; wherein the first matrix is ​​composed of the remaining data of the data sample after removing all the data of the operation scheme where the missing data is located and the corresponding secondary indicators, and the first vector is composed of all the normal data in the operation scheme where the missing data is located; The value of the missing data is determined based on the product of the second vector and the coefficient vector; wherein the second vector is composed of all normal data of the secondary indicators corresponding to the missing data.

4. The method according to claim 1, characterized in that: The normalizing each data in the data sample comprises: For the data corresponding to the secondary indicators belonging to positive indicators, the following formula is used for normalization: ; For the data corresponding to the secondary indicators that are negative indicators, the following formula is used for normalization: ; Where X ij The data of the jth secondary indicator of the i-th operation plan, S ij Represents X ij After normalization, max(x j ) represents the maximum value of the j-th secondary index, min(x j ) represents the minimum value of the j-th secondary index.

5. The method according to claim 1, characterized in that Determining the weight coefficient of each secondary indicator includes: The weight coefficient of each secondary indicator is determined by the CRITIC method.

6. The method according to claim 1, characterized in that Also includes: Based on the comprehensive score and the preset stability evaluation level comparison table, the stability level of each operation scheme is determined.

7. The method according to claim 1, characterized in that The first-level indicators include frequency stability, economic cost and renewable energy utilization rate; the multiple second-level indicators of frequency stability include frequency response time, frequency regulation capability and frequency fluctuation amplitude; the multiple second-level indicators of economic cost include system construction cost, operation and maintenance cost and economic rate of return; the multiple second-level indicators of renewable energy utilization rate include renewable energy penetration rate, energy storage system utilization rate and carbon emission reduction benefits.

8. A new energy inertia stability evaluation device with strong robustness and multi-objective consideration, characterized in that: include: A setting module, used to set a plurality of primary indicators for evaluating stability and a plurality of secondary indicators included in each of the primary indicators; A normalization module, used to normalize each data in the data sample; wherein the data sample includes data of multiple operation schemes of the new energy power grid, and the data of each operation scheme includes all the secondary indicators; A weight module, used to determine the weight coefficient of each of the secondary indicators; A scoring module is used to determine a comprehensive score for the stability of each of the operating schemes based on the normalized data of the data samples and the weight coefficient of each of the secondary indicators.

9. An electronic device, characterized in that: include: one or more processors; as well as A memory storing computer executable instructions, wherein when the computer executable instructions are executed by the one or more processors, the one or more processors execute the new energy inertia stability evaluation method with strong robustness and considering multiple objectives as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by a computer, the new energy inertia stability evaluation method with strong robustness and considering multiple objectives according to any one of claims 1 to 7 is implemented.

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