Thermal power generating unit flexibility analysis method and system based on triangular similarity

Abstract

The invention discloses a thermal power generating unit flexibility evaluation method and system based on triangular similarity, and belongs to the field of thermal power generating unit flexibility analysis. The invention discloses a thermal power generating unit flexibility evaluation method based on triangular similarity. The method comprises the following steps: step 1, calculating thermal power generating unit flexibility effect index data; 2, preprocessing the flexibility data matrix; 3, calculating the weight of each effect index, and normalizing the matrix; 4, calculating a positive ideal solution and a negative ideal solution; 5, calculating a dimensionless processing value of the distance between each effect index and the positive and negative ideal solutions thereof to obtain a thermal power generating unit flexibility quantitative value; 6, ranking the power generation capacity and verifying a result; according to the method, the flexibility effect index system of the thermal power generating unit is constructed, and the flexibility difference information of each unit is measured by adopting the triangular similarity, so that the capability of judging the advantages and disadvantages of solutions is improved, and an effective analysis method is provided for the flexibility of the thermal power generating unit.

Description

Technical Field

[0001] The present invention relates to the technical field of flexibility analysis of thermal power units, and in particular to a flexibility analysis method and system for thermal power units based on triangle similarity. Background Art

[0002] It is important and urgent to conduct flexibility analysis of thermal power units, which is directly related to the optimization of energy structure and the safe and stable operation of power system.

[0003] Patent CN117592801A comprehensively considers economy, technology, regulation capacity, production parameters, environment and multi-level confirmation of power grid operation, and proposes an evaluation method for the comprehensive value of thermal power unit flexibility transformation technology; Patent CN116561531A constructs a thermal power unit flexibility operation index system from the aspects of safety and flexibility, uses expert scoring hierarchical analysis method to assign weights to indicators, and proposes a comprehensive performance evaluation method for the flexibility operation mode of thermal power units. CN114926085A uses the information entropy weight method to calculate the weight of the thermal power unit regulation capacity index, and proposes a data-driven thermal power unit regulation capacity evaluation method and system. However, the above-mentioned traditional analysis methods currently mainly rely on empirical judgment and qualitative analysis, and lack quantitative evaluation methods; with the development of computing technology, some data-driven methods have been proposed, but these methods often require a large amount of historical data and have certain limitations when dealing with nonlinear and complex systems.

[0004] In response to the above problems, this patent proposes a method and system for analyzing the flexibility of thermal power units based on triangle similarity. Summary of the invention

[0005] The purpose of the present invention is to solve the problems existing in the prior art and to propose a method and system for analyzing the flexibility of thermal power units based on triangle similarity.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A method for analyzing the flexibility of a thermal power unit based on triangular similarity, characterized by comprising the following steps:

[0008] Step 1: Collect the data of flexibility index of power generation capacity of thermal power units in the region to form a flexibility index data matrix;

[0009] Step 2, normalizing the data matrix obtained in step 1 to obtain a normalized matrix of each flexibility index;

[0010] Step 3, according to the normalized matrix obtained in step 2, the weight of each flexibility index is calculated, and the normalized matrix is ​​further calculated;

[0011] Step 4, calculate the positive and negative ideal solutions according to the normalized matrix obtained in step 3;

[0012] Step 5: According to the positive and negative ideal solutions obtained in step 4, the dimensionless processed value of the distance between each flexibility index and its positive and negative ideal solutions is calculated based on the relative closeness of the thermal power units based on the triangular similarity;

[0013] Step six: rank the flexibility adjustment capabilities and verify the results.

[0014] Preferably, in step 1, the flexibility index includes maximum regulation rate, minimum stable output, cold start time, hot start time, response time, regulation time, and regulation accuracy;

[0015] The maximum regulation rate refers to the maximum ramp speed of the unit output per minute; the minimum stable output refers to the output size of the unit when it is at minimum stable combustion; the cold start time refers to the minimum time required for the unit to operate at full load from the complete stop of the unit and the ignition of the boiler when the main equipment such as the boiler and the turbine have been completely cooled to the ambient temperature; the hot start time refers to the time required to restart and restore to full load operation after the unit is shut down and the boiler still maintains a certain temperature, that is, when the boiler has not completely cooled to the ambient temperature; the response time refers to the time delay of the thermal power unit in responding to the AGC control command, that is, the time required from the power grid issuing the frequency regulation command to the unit starting to respond to this change; the regulation time refers to the time it takes for the thermal power unit to execute the AGC control command, that is, the time required from the power grid issuing the frequency regulation command to the unit completing the command change; the regulation accuracy refers to the accuracy of the power generation unit in responding to the AGC command;

[0016] Preferably, in step 2, the calculation method of the flexibility index data normalization matrix is:

[0017]

[0018] Where B is the normalized matrix of flexibility index data, m and n represent the number of thermal power units and the number of flexibility indexes, respectively, i = 1, 2, ..., m represents the i-th thermal power unit, j = 1, 2, ..., n represents the j-th flexibility index, and the matrix element b is ij Calculate according to the following formula:

[0019]

[0020] Where b ij represents the normalized result of each flexibility index, a ij Represents the original data value of the j-th flexibility index of the ith thermal power unit.

[0021] Preferably, the indicator weight calculation method in step 3 is:

[0022]

[0023] in w j is the weight of the j-th flexibility index;

[0024] Based on w j and b ij Compute the matrix:

[0025]

[0026] x ij Represents the element in the i-th row and j-th column, where i=1,2,…,m represents the i-th thermal power unit and j=1,2,…,n represents the j-th flexibility index.

[0027] Preferably, in step 4, the positive and negative ideal solutions are calculated based on the normalized matrix as follows:

[0028]

[0029] In the formula, It means taking the maximum value of the j-th flexibility index of each object; It means taking the minimum value of the j-th flexibility index of each object; represents the positive ideal solution, represents a negative ideal solution.

[0030] Preferably, in step 5, the method for calculating the triangular similarity is:

[0031]

[0032]

[0033] in, Indicates positive and negative triangle similarity, Respectively represent X + , X - The jth element in ; is the mean of the positive and negative ideal values ​​of the jth flexibility index; e = 2.7182818 is a mathematical symbol representing the base of the natural logarithm; the symbol sim(*,*) represents: a=[a1,…,a n ] T ; b=[b1,…,b n ] T .

[0034] Preferably, in step 5, the calculation method of the flexibility of the thermal power unit based on triangle similarity is:

[0035]

[0036] In the formula, Respectively represent the dimensionless processing value of the flexibility of each thermal power unit.

[0037] Preferably, in step six, the calculation method for verifying the flexibility adjustment ability ranking result is:

[0038] A. First, the comprehensive analysis value Z = (z1, z2, ..., z m ) T Arrange in order from smallest to largest

[0039] B. Secondly, calculate the difference between any two adjacent analysis values use Indicates the degree of distinction between two adjacent analysis values, using Indicates the degree of distinction between the maximum and minimum values;

[0040] C. Finally, and The sum represents the total discrimination, and dividing by m can eliminate the influence of the number of analysis values ​​on the result and obtain the discrimination of the comprehensive analysis value. The method for calculating the discrimination of the comprehensive analysis value is:

[0041]

[0042] Where D represents the discrimination of the comprehensive analysis value.

[0043] A thermal power unit flexibility analysis system based on triangle similarity includes a thermal power unit flexibility analysis method based on triangle similarity.

[0044] Compared with the prior art, the present invention provides a method and system for analyzing the flexibility of thermal power units based on triangular similarity, which has the following beneficial effects:

[0045] 1. This method of analyzing the flexibility of thermal power units based on triangular similarity quantifies the performance changes of thermal power units under different operating conditions and uses the mathematical tool of triangular similarity to evaluate the flexibility of thermal power units, thereby providing a scientific basis for the optimal scheduling of power systems and the transformation and upgrading of thermal power units. The proposal of this method not only responds to the national policy requirements on energy transformation and improving the flexibility of power systems, but also provides technical support for the sustainable development of the power industry.

[0046] 2. The flexibility analysis method of thermal power units based on triangular similarity uses the coefficient of variation to measure the difference information within the index, which can truly reflect the difference information size of the numerical value within the index and enhance the influence of the difference within the index on the weight.

[0047] 3. The flexibility analysis method of thermal power units based on triangular similarity improves the distance analysis by adopting improved grey correlation analysis, thereby enhancing the ability to judge the quality of the solution.

[0048] 4. The flexibility analysis method of thermal power units based on triangle similarity verifies the robustness and effectiveness of the proposed method by analyzing the stability of the sorting results; and verifies the correctness and effectiveness of the method proposed in this paper through two groups of specific implementation methods, providing an effective analysis method for the power capacity of thermal power units. DETAILED DESCRIPTION

[0049] The technical solutions in the embodiments of the present invention will be described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0050] In the description of the present invention, it is necessary to understand that the terms "upper", "lower", "front", "back", "left", "right", "top", "bottom", "inside", "outside", etc., indicating directions or positional relationships, are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as a limitation on the present invention.

[0051] In order to illustrate the accuracy and effectiveness of the algorithm proposed in the present invention, Example 1 and Example 2 are used for emphasizing the description. Example 1 uses simulated data to illustrate the accuracy of the algorithm, and Example 2 uses real data to illustrate the effectiveness of the algorithm.

[0052] Embodiment 1:

[0053] Step 1: Collect the data of flexibility index of power generation capacity of thermal power units in the region to form a flexibility index data matrix;

[0054] In step 1, there are 6 units and 6 indicators, and the original data of each thermal power unit are shown in Table 1;

[0055] Table 1. Raw data

[0056] Unit Name T1 T2 T3 T4 T5 T6 Unit 1 0.01 500 0.1 40 1 10 Unit 2 0.02 500 0.1 40 1 10 Unit 3 0.02 700 0.1 40 1 10 Unit 4 0.02 700 0.2 40 1 10 Unit 5 0.02 700 0.2 50 1 20 Unit 6 0.02 700 0.2 50 2 10

[0057] The simulation index data includes index data of different orders of magnitude. The T1-T4 performance indicators change from small to large in the order of units 1-6, and only one indicator changes between units, to verify the impact of different indicator changes on the ranking of units 1-6; at the same time, the T5 and T6 indicators are set to change only by the same multiples between units 5 and 6, to verify the impact of the optimal indicator change on the unit ranking.

[0058] Step 2, normalizing the data matrix obtained in step 1 to obtain a normalized matrix of each flexibility index;

[0059] In step 2, each performance indicator data is preprocessed to obtain a normalized matrix of performance indicator data, which is calculated as follows:

[0060]

[0061] Where B is the normalized matrix of performance index data, m and n represent the number of thermal power units and the number of performance indicators respectively, i = 1, 2, ..., m represents the i-th thermal power unit, j = 1, 2, ..., n represents the j-th performance indicator, and the matrix element b ij It is calculated by applying the vector norm method as follows:

[0062]

[0063] Where b ij Represents the normalized result of each performance indicator, a ij Represents the original data value of the jth performance indicator of the ith thermal power unit.

[0064] It should be noted that adding 10 -10 It can prevent max(a ij ) is 0, the result is abnormal, but it does not affect the normal calculation. The calculation results are shown in Table 2:

[0065] Table 2 Normalized matrix

[0066]

[0067]

[0068] Step 3, according to the normalized matrix obtained in step 2, the weight of each flexibility index is calculated, and the normalized matrix is ​​further calculated;

[0069] In step 3, the weight w of the jth performance indicator is j The calculation method is:

[0070]

[0071] in The calculation results of each indicator weight are shown in Table 3.

[0072] Table 3 Weight of each indicator

[0073] T1 T2 T3 T4 T5 T6 0.142 0.104 0.233 0.076 0.223 0.223

[0074] The method to calculate the normalized matrix is:

[0075]

[0076] Table 4 Normalized weight matrix

[0077] Unit Name T1 T2 T3 T4 T5 T6 Unit 1 0.071 0.074 0.116 0.061 0.111 0.111 Unit 2 0.142 0.074 0.116 0.061 0.111 0.111 Unit 3 0.142 0.104 0.116 0.061 0.111 0.111 Unit 4 0.142 0.104 0.233 0.061 0.111 0.111 Unit 5 0.142 0.104 0.233 0.076 0.111 0.223 Unit 6 0.142 0.104 0.233 0.076 0.223 0.111

[0078] Step 4, calculate the positive and negative ideal solutions according to the normalized matrix obtained in step 3;

[0079] In step 4, based on the normalized matrix, the positive and negative ideal solutions are calculated as follows:

[0080]

[0081] In the formula, Indicates taking the maximum value of each indicator; Indicates taking the minimum value of each indicator; represents the positive ideal solution, represents the negative ideal solution. The results are shown in Table 5.

[0082] Table 5 Ideal solution

[0083] T1 T2 T3 T4 T5 T6 The ideal solution 0.142 0.104 0.233 0.076 0.223 0.223 Negative ideal solution 0.071 0.074 0.116 0.061 0.111 0.111

[0084] Step 5: According to the positive and negative ideal solutions obtained in step 4, the dimensionless processed value of the distance between each flexibility index and its positive and negative ideal solutions is calculated based on the relative closeness of the thermal power units based on the triangular similarity;

[0085] In step 5, the method for calculating the triangular similarity is:

[0086]

[0087] in, Indicates positive and negative triangle similarity, Respectively represent X + , X - The jth element in ; is the mean of the positive and negative ideal values ​​of the jth indicator; e = 2.7182818 is a mathematical symbol representing the base of the natural logarithm. The symbol sim(*,*) means: a=[a1,…,a n ] T ; b=[b1,…,b n ] T .

[0088] The calculation method of thermal power unit flexibility based on triangular similarity is:

[0089]

[0090] In the formula, Respectively represent the distance between each indicator and its positive ideal solution and negative ideal solution The dimensionless processed values ​​are shown in Table 6.

[0091] Table 6 Calculation results

[0092]

[0093] From the ranking results, the ranking order of units 1 to 6 changes from small to large, which is in line with the overall ranking result expectations of the simulation data; the ranking results between units 2 and 3 change slightly, while the ranking results of other units change greatly, which can be concluded from the normalized weighted matrix table 4 that unit 3 changes only by 0.03 on indicator T2 compared with unit 2, which is relatively small compared with the change of 0.071 on T1 for unit 2 and the change of 0.117 on T3 for unit 4 compared with unit 3, so the change of its capacity ranking is small, while the ranking results of other units change greatly; in addition, although units 5 and 6 have changes in indicators T5 and T6, the data variation degree of T5 and T6 indicators is the same, and the indicator weights are the same, so the indicator results are the same, which is consistent with the result that the ranking results should be consistent with the fact that units 5 and 6 occupy one of the best values ​​and one of the worst values ​​respectively.

[0094] Step 6: rank the flexibility adjustment capabilities and verify the results;

[0095] In step 6, the calculation method for verifying the ranking results of flexibility adjustment ability is:

[0096] A. First, the comprehensive analysis value Z = (z1, z2, ..., z m ) T Arrange in order from smallest to largest

[0097] B. Secondly, calculate the difference between any two adjacent analysis values use Indicates the degree of distinction between two adjacent analysis values, using Indicates the degree of distinction between the maximum and minimum values;

[0098] C. Finally, and The sum represents the total discrimination, and dividing by m can eliminate the influence of the number of analysis values ​​on the result and obtain the discrimination of the comprehensive analysis value.

[0099] In step C, the method for calculating the discrimination of the comprehensive analysis value is:

[0100]

[0101] Wherein, D represents the discrimination degree of the comprehensive analysis value, and the discrimination degree of the present invention is 0.212, indicating that it has a good sorting and discrimination effect.

[0102] In the traditional Euclidean distance calculation In the method, the calculation method is usually taken as

[0103]

[0104] This method determines the quality of a unit by calculating the distance between each indicator of the unit and the ideal solution. If a unit has multiple analysis indicators, when some indicators of multiple units have different values ​​but the same distance from the ideal solution, it will be impossible to determine the quality of the unit. replace Under the condition that other calculation processes remain unchanged, the discrimination degree is 0.181, which indicates that when the Euclidean distance is used to calculate the distance between the various indicators of the analyzed unit and the ideal solution, the Euclidean distance has a certain failure defect when the indicators have a certain linear correlation. The present invention uses triangular similarity to weaken the influence of the similarity between indicators on the results, improves the defect that the Euclidean distance fails when there is a correlation between the calculated indicators, and further improves the discrimination degree of the analyzed unit.

[0105] Comprehensive analysis is a multi-step task, and changes in any step will have an impact on the results of the comprehensive analysis. Since different analysis indicators and models represent different analysis purposes and mechanisms, it is reasonable that the analysis results are different due to changes in analysis indicators or models. However, when the comprehensive analysis indicator system and model are certain, it is unreasonable that the comprehensive analysis results are reversed due to local changes in samples, unit changes, or different data processing methods. Therefore, the volatility of the comprehensive analysis results caused by local changes in samples, unit changes, and different dimensionless methods is called the stability of the comprehensive analysis results. This paper uses stability to reflect the robustness and effectiveness of the proposed method.

[0106] Embodiment 2:

[0107] Step 1, collect the flexibility index of the flexibility adjustment capability of 10 thermal power units in the region, including flexibility index, maximum adjustment rate (% / min), minimum stable output (%), cold start time (h), hot start time (h), response time (s), adjustment time (s), adjustment accuracy (%), among which the inverse of the original data of minimum stable output, cold start time, hot start time, response time, adjustment time, and adjustment accuracy is calculated as the index data. That is, the original index data matrix A=[a ij ] m×n, i=1,2,…,m represents the i-th thermal power unit, j=1,2,…,n represents the j-th flexibility index. As shown in Table 7.

[0108] Table 7 Flexibility index raw data

[0109]

[0110] Step 2: pre-process the data of various flexibility indicators to obtain a normalized matrix of flexibility indicator data, the calculation method of which is:

[0111]

[0112] Where B is the normalized matrix of flexibility index data, m and n represent the number of thermal power units and the number of flexibility indexes, respectively, i = 1, 2, ..., m represents the i-th thermal power unit, j = 1, 2, ..., n represents the j-th flexibility index, and the matrix element b is ij It is calculated by applying the vector norm method as follows:

[0113]

[0114] Where b ij represents the normalized result of each flexibility index, a ij represents the original data value of the jth flexibility index of the i-th thermal power unit. It should be noted that adding 10 -10 It can prevent max(a ij ) is 0, the result is abnormal, but it does not affect normal calculation.

[0115] Step 3: The weight calculation method of each flexibility indicator is:

[0116]

[0117] in w j is the weight of the jth flexibility index. The calculation results are shown in Table 8.

[0118] Table 8 Weights of each indicator

[0119]

[0120] Step 4, based on w j and b ij Compute the matrix:

[0121]

[0122] x ijrepresents the element in the i-th row and j-th column, where i=1,2,…,m represents the i-th thermal power unit and j=1,2,…,n represents the j-th flexibility index. And calculate the positive and negative ideal solutions:

[0123]

[0124] In the formula, It means taking the maximum value of the j-th flexibility index of each object; It means taking the minimum value of the j-th flexibility index of each object; represents the positive ideal solution, represents a negative ideal solution.

[0125] Step 5, based on the relative proximity of the thermal power units of the triangle similarity, the dimensionless processed value of the distance between each flexibility index and its positive and negative ideal solutions is calculated;

[0126]

[0127] in, Indicates positive and negative triangle similarity, Respectively represent X + , X - The jth element in ; is the mean of the positive and negative ideal values ​​of the jth flexibility index; e = 2.7182818 is a mathematical symbol representing the base of the natural logarithm. The symbol sim(*,*) means: a=[a1,…,a n ] T ; b=[b1,…,b n ] T .

[0128] Step 6: The calculation method of thermal power unit flexibility based on triangle similarity is:

[0129]

[0130] In the formula, They represent the dimensionless processing value of the flexibility of each thermal power unit. The results are shown in Table 9.

[0131] Table 9 Final sorting results;

[0132]

[0133] From the results, it can be seen that unit 2 has better flexibility, while units 4 and 10 have poorer flexibility. Although unit 4 has better maximum regulation rate and regulation accuracy, while unit 10 has better maximum regulation rate and minimum stable output than unit 2, the performance of unit 2 is better than that of units 4 and 10 in other indicators, and the weights of the indicators of maximum regulation rate, regulation accuracy and minimum stable output are smaller, as shown in Table 9. Therefore, the ranking value of unit 2 is higher than that of units 4 and 10, which verifies the rationality and effectiveness of the algorithm.

[0134] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for analyzing the flexibility of thermal power units based on triangular similarity, characterized in that: The steps include: Step 1: Calculate the flexibility index data of the power generation capacity of thermal power units in the region to form a flexibility index data matrix; Step 2, normalizing the data matrix obtained in step 1 to obtain a normalized matrix of each flexibility index; Step 3, according to the normalized matrix obtained in step 2, the weight of each flexibility index is calculated, and the normalized matrix is ​​further calculated; Step 4, calculate the positive and negative ideal solutions according to the normalized matrix obtained in step 3; Step 5: According to the positive and negative ideal solutions obtained in step 4, the dimensionless processed value of the distance between each flexibility index and its positive and negative ideal solutions is calculated based on the relative closeness of the thermal power units based on the triangular similarity; Step six: rank the flexibility adjustment capabilities and verify the results.

2. A method for analyzing the flexibility of thermal power units based on triangular similarity according to claim 1, characterized in that: In step 1, the flexibility indicators include maximum regulation rate, minimum stable output, cold start time, hot start time, response time, regulation time, and regulation accuracy; The maximum regulation rate indicates the maximum ramp speed of the unit output per minute; the minimum stable output indicates the output size of the unit at the minimum stable combustion; the cold start time indicates the minimum time required from the complete shutdown of the unit and the ignition of the boiler to full load operation after the boiler, steam turbine and other major equipment have been completely cooled to the ambient temperature; the hot start time indicates the time required to restart and restore to full load operation after the unit is shut down and the boiler still maintains a certain temperature, that is, the time required for the boiler to be restarted and restored to full load operation when it has not completely cooled to the ambient temperature; the response time refers to the time delay of the thermal power unit in responding to the AGC control command, that is, the time required from the power grid issuing the frequency regulation command to the unit starting to respond to this change; the regulation time refers to the time it takes for the thermal power unit to execute the AGC control command, that is, the time required from the power grid issuing the frequency regulation command to the unit completing the command change; the regulation accuracy refers to the accuracy of the power generation unit in responding to the AGC command; The reciprocals of the original data of the minimum stable output, cold start time, hot start time, response time, regulation time and regulation accuracy are calculated as the original indicator data.

3. The method for analyzing the flexibility of thermal power units based on triangular similarity according to claim 1 is characterized in that: In step 2, the calculation method of the normalized matrix of flexibility index data is: Where B is the normalized matrix of flexibility index data, m and n represent the number of thermal power units and the number of flexibility indexes, respectively, i = 1, 2, ..., m represents the i-th thermal power unit, j = 1, 2, ..., n represents the j-th flexibility index, and the matrix element b is ij Calculate according to the following formula: Where b ij represents the normalized result of each flexibility index, a ij Represents the original data value of the j-th flexibility index of the ith thermal power unit.

4. The method for analyzing the flexibility of thermal power units based on triangular similarity according to claim 3 is characterized in that: The indicator weight calculation method in step 3 is: in is the weight of the j-th flexibility index; Based on w j and b ij Compute the matrix: x ij Represents the element in the i-th row and j-th column, where i=1, 2,…, m represents the i-th thermal power unit, and j=1, 2,…, n represents the j-th flexibility index.

5. The method for analyzing the flexibility of thermal power units based on triangular similarity according to claim 1 is characterized in that: In step 4, based on the normalized matrix, the positive and negative ideal solutions are calculated as follows: In the formula, It means taking the maximum value of the j-th flexibility index of each object; It means taking the minimum value of the j-th flexibility index of each object; represents the positive ideal solution, represents a negative ideal solution.

6. A method for analyzing the flexibility of thermal power units based on triangular similarity according to claim 5, characterized in that: In step 5, the method for calculating the triangular similarity is: in, Indicates positive and negative triangle similarity, Respectively represent X + , X - The jth element in ; is the mean of the positive and negative ideal values ​​of the j-th flexibility index; e = 2.7182818 is a mathematical symbol representing the base of the natural logarithm; the symbol sim(*, *) represents: a=[a1,…,a n ] T ; b = [b1, ..., b n ] T .

7. The method for analyzing the flexibility of thermal power units based on triangular similarity according to claim 1, characterized in that: In step 5, the calculation method of thermal power unit flexibility based on triangle similarity is: In the formula, Respectively represent the dimensionless processing value of the flexibility of each thermal power unit.

8. The method for analyzing the flexibility of thermal power units based on triangular similarity according to claim 1 is characterized in that: In step 6, the calculation method for verifying the ranking results of flexibility adjustment ability is: A. First, the comprehensive analysis value Z = (z1, z2, ..., z m ) T Arrange in order from smallest to largest B. Secondly, calculate the difference between any two adjacent analysis values use Indicates the degree of distinction between two adjacent analysis values, using Indicates the degree of distinction between the maximum and minimum values; C. Finally, and The sum represents the total discrimination, and dividing by m can eliminate the influence of the number of analysis values ​​on the result and obtain the discrimination of the comprehensive analysis value. The method for calculating the discrimination of the comprehensive analysis value is: Where D represents the discrimination of the comprehensive analysis value.

9. A thermal power unit flexibility analysis system based on triangular similarity, characterized in that: A method for analyzing the flexibility of thermal power units based on triangular similarity as described in any one of claims 1 to 8.

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