Efficiency evaluation method of supercritical carbon dioxide Brayton cycle system

Abstract

The invention discloses an efficiency evaluation method for a supercritical carbon dioxide Brayton cycle system, and relates to the technical field of energy conversion system evaluation, and the method comprises the steps: building an evaluation hierarchical structure model according to the evaluation indexes of the supercritical carbon dioxide Brayton cycle system; constructing a judgment matrix based on each index element and the corresponding proportion scale in the evaluation hierarchical structure model; calculating the weight of each index element in the judgment matrix, and carrying out quantitative analysis on the efficiency of the supercritical carbon dioxide Brayton cycle system; performing qualitative analysis on the efficiency of the supercritical carbon dioxide Brayton cycle system; according to the method, the supercritical carbon dioxide Brayton cycle system can be evaluated and optimized.

Description

Technical Field

[0001] The invention relates to the technical field of energy conversion system evaluation, and in particular to an efficiency evaluation method for a supercritical carbon dioxide Brayton cycle system. Background Art

[0002] Supercritical carbon dioxide has significant advantages such as low critical parameters, high power density, good heat transfer performance, non-toxic stability, and low cost and easy availability. It is a high-quality energy transmission and power conversion working fluid. The supercritical carbon dioxide Brayton cycle system is a power cycle form that has attracted widespread attention at home and abroad in recent years. It has the advantages of high cycle efficiency, low compression power consumption, small system size, and great cost reduction potential. It can be combined with various forms of heat sources. At present, experts and scholars at home and abroad have conducted research on the application of this technology in different fields.

[0003] At the same time, the evaluation of supercritical carbon dioxide Brayton cycle systems is also being gradually carried out, mostly focusing on system economy, energy saving and emission reduction, but in special application scenarios, "efficiency" is often a more concerned indicator; among them, efficiency is defined as the ability to achieve specified usage objectives under specified conditions.

[0004] A Chinese patent (CN109508851B) discloses a comprehensive performance evaluation method for a small lead-based reactor supercritical carbon dioxide cycle power generation system. By integrating multiple disciplines such as thermodynamics, heat transfer, fluid dynamics and economics, it is suitable for the design and comprehensive performance evaluation of power generation systems with different operating parameter levels; however, there is still a lack of performance evaluation in the power generation system;

[0005] In response to the technical gaps in the above-mentioned contents, this paper takes the supercritical carbon dioxide Brayton cycle system as the object, and proposes a performance evaluation method based on the general quality characteristics and special quality characteristics of the system, which can be used to support the evaluation and optimization of the supercritical carbon dioxide Brayton cycle system. Summary of the invention

[0006] In order to overcome the deficiencies in the background technology, the present invention discloses a method for evaluating the performance of a supercritical carbon dioxide Brayton cycle system.

[0007] In order to achieve the above-mentioned invention object, the present invention adopts the following technical scheme:

[0008] A method for evaluating the performance of a supercritical carbon dioxide Brayton cycle system, comprising the following specific steps:

[0009] According to the evaluation indexes of supercritical carbon dioxide Brayton cycle system, an evaluation hierarchy model is established;

[0010] Based on the various indicator elements and corresponding scales in the evaluation hierarchy model, a judgment matrix is ​​constructed;

[0011] Calculate the weight of each indicator element in the judgment matrix and conduct a quantitative analysis of the efficiency of the supercritical carbon dioxide Brayton cycle system;

[0012] Qualitative analysis of the performance of the supercritical carbon dioxide Brayton cycle system was conducted.

[0013] Preferably, the evaluation hierarchy includes a system layer, an element layer and an indicator layer, wherein the system layer includes dedicated quality characteristics and general quality characteristics;

[0014] The element layer of the dedicated quality characteristics includes energy saving, flexibility, compactness and economy; the index layer of energy saving includes energy conversion efficiency and compressed power consumption; the index layer of flexibility includes start-stop time and operating condition change rate; the index layer of compactness includes unit power volume; the index layer of economy includes specific power cost;

[0015] The element layer of the general quality characteristics includes reliability, maintainability, safety, security, testability and environmental adaptability; the indicator layer of the reliability includes mean time before failure / failure, mean time between failures, mean time between serious failures, mean time between maintenance, service life, reliable life, storage life and first overhaul period; the indicator layer of the maintainability includes mean repair time, mean preventive maintenance time, important component replacement time and standardization rate; the indicator layer of the safety includes risk rate, accident rate and safety degree; the indicator layer of the security includes average security delay time, average management delay time, security equipment satisfaction rate, security equipment utilization rate, spare parts satisfaction rate and spare parts utilization rate; the indicator layer of the testability includes fault detection rate, fault isolation rate and false alarm rate; the indicator layer of the environmental adaptability includes natural environment adaptability and induced environment adaptability.

[0016] Preferably, the weight calculation of each indicator element in the judgment matrix adopts the hierarchical analysis method.

[0017] Preferably, the specific steps of the analytic hierarchy process are:

[0018] 1) Obtain the maximum eigenvalue λ of the judgment matrix and its corresponding eigenvector;

[0019] 2) Normalize the feature vector to obtain the corresponding weight w;

[0020] 3) Perform consistency check on the judgment matrix;

[0021] 4) After the consistency test is passed, the weight of each indicator element for the supercritical carbon dioxide Brayton cycle system is calculated.

[0022] Preferably, the specific steps of the consistency check are:

[0023] 3.1) Calculate the consistency index CI as:

[0024]

[0025] Where: λ is the maximum characteristic root of the judgment matrix; n is the order of the judgment matrix

[0026] 3.2) The consistency index RI is introduced, and the calculation formula of RI is:

[0027]

[0028] 3.3) The consistency deviation degree of the judgment matrix is ​​tested by the test coefficient CR. The specific calculation formula is:

[0029]

[0030] Preferably, the weight calculation formula of each index element for the supercritical carbon dioxide Brayton cycle system is:

[0031]

[0032] Preferably, the qualitative analysis of the efficiency of the supercritical carbon dioxide Brayton cycle system adopts a fuzzy comprehensive evaluation method.

[0033] Preferably, the specific steps of the fuzzy comprehensive evaluation method are:

[0034] 1) Construct evaluation factor data set;

[0035] 2) Constructing a review collection;

[0036] 3) Calculate the index membership based on the comment set and the evaluation factor data set;

[0037] 4) Determine the fuzzy matrix according to the membership value of the indicator;

[0038] 5) Calculate the evaluation vector based on the fuzzy matrix;

[0039] 6) Calculate the efficiency of the supercritical carbon dioxide Brayton cycle system.

[0040] Preferably, the evaluation factor dataset E p ={E p,1 , E p,2 , …, E p,q}, where p is the specific number of layers in the evaluation hierarchy model, and q is the number of indicators in that layer.

[0041] Preferably, the review set is {very good, good, average, very bad, poor}.

[0042] Due to the adoption of the above-mentioned technical solution, the present invention has the following beneficial effects:

[0043] The present invention discloses a method for evaluating the performance of a supercritical carbon dioxide Brayton cycle system, which can effectively improve the accuracy of the final performance evaluation result by using quantitative and qualitative methods to evaluate the performance of the supercritical carbon dioxide Brayton cycle system.

[0044] Starting from the general quality characteristics and special quality characteristics, a variety of factors and indicators are combined to jointly establish a performance evaluation hierarchical model, making the calculation process more detailed, thereby further improving the accuracy of the calculation results;

[0045] In addition, this method can be used to support comparative analysis between different technical solutions, thereby further optimizing the system solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 A structural schematic diagram of the present invention;

[0047] Figure 2 It is a schematic diagram of the composition of the evaluation hierarchy model;

[0048] Figure 3 Schematic diagram of the distribution of attraction domain and repulsion domain;

[0049] Figure 4 A schematic diagram of a performance review collection. DETAILED DESCRIPTION

[0050] The technical solution of the present invention will be described below in conjunction with the drawings in the embodiments of the present invention. In the description, it should be understood that if there are terms such as "upper", "lower", "front", "back", "left", "right" and the like indicating directions or positional relationships, they are only corresponding to the drawings of the present invention, for the convenience of describing the present invention, and do not indicate or imply that the devices or components referred to must have a specific direction:

[0051] Embodiment 1 is:

[0052] Combined with Figure 1 The efficiency evaluation method of a supercritical carbon dioxide Brayton cycle system comprises the following specific steps:

[0053] According to the evaluation index of supercritical carbon dioxide Brayton cycle system, an evaluation hierarchical structure model is established; based on each index element and the corresponding scale in the evaluation hierarchical structure model, a judgment matrix is ​​constructed; the corresponding scale of the index element is shown in the following table

[0054] Table 1 Ratio scale table

[0055]

[0056] Calculate the weight of each indicator element in the judgment matrix and conduct a quantitative analysis of the efficiency of the supercritical carbon dioxide Brayton cycle system;

[0057] Qualitative analysis of the performance of the supercritical carbon dioxide Brayton cycle system was conducted.

[0058] Embodiment 2 is:

[0059] Based on Example 1, Figure 2 , further defining the evaluation hierarchy model, that is, the evaluation hierarchy model includes a system layer, an element layer and an indicator layer, wherein the system layer includes dedicated quality characteristics and general quality characteristics;

[0060] The element layer of the dedicated quality characteristics includes energy saving, flexibility, compactness and economy; the index layer of energy saving includes energy conversion efficiency and compressed power consumption; the index layer of flexibility includes start-stop time and operating condition change rate; the index layer of compactness includes unit power volume; the index layer of economy includes specific power cost;

[0061] The element layer of the general quality characteristics includes reliability, maintainability, safety, security, testability and environmental adaptability; the indicator layer of the reliability includes mean time before failure / failure, mean time between failures, mean time between serious failures, mean time between maintenance, service life, reliable life, storage life and first overhaul period; the indicator layer of the maintainability includes mean repair time, mean preventive maintenance time, important component replacement time and standardization rate; the indicator layer of the safety includes risk rate, accident rate and safety degree; the indicator layer of the security includes average security delay time, average management delay time, security equipment satisfaction rate, security equipment utilization rate, spare parts satisfaction rate and spare parts utilization rate; the indicator layer of the testability includes fault detection rate, fault isolation rate and false alarm rate; the indicator layer of the environmental adaptability includes natural environment adaptability and induced environment adaptability.

[0062] Embodiment 3 is:

[0063] On the basis of Example 1, the weight calculation of each indicator element in the judgment matrix adopts the hierarchical analysis method.

[0064] According to the needs, the specific steps of the hierarchical analysis method are:

[0065] 1) Obtain the maximum eigenvalue λ of the judgment matrix and its corresponding eigenvector;

[0066] The method used is the eigenvalue calculation method;

[0067] 2) Normalize the feature vector to obtain the corresponding weight w;

[0068] That is, step 1) and step 2) are the hierarchical single sorting process in the hierarchical analysis method, and according to the positive matrix theory, the parameters of the judgment matrix should have the following characteristics:

[0069] a ii =1;

[0070]

[0071] 3) Perform consistency check on the judgment matrix;

[0072] The reason for consistency check is: in the process of establishing the judgment matrix, it is impossible to achieve complete consistency in the comparison between the two, which will lead to deviation in the weight calculation results. In order to avoid excessive errors and affect the accuracy of calculation, consistency check is required;

[0073] The specific steps of consistency check are:

[0074] 3.1) Calculate the consistency index CI as:

[0075]

[0076] In the formula: λ is the maximum characteristic root of the judgment matrix; n is the order of the judgment matrix;

[0077] CI = 0, completely consistent; CI is close to 0, meeting the consistency test requirements; the larger λ is than n, the larger CI is, and the more serious the inconsistency of the matrix is;

[0078] 3.2) In order to judge whether CI meets the requirements, the consistency index RI is introduced, and the calculation formula of RI is:

[0079]

[0080] RI is mainly affected by the order of the judgment matrix. The larger the order, the larger the random consistency index RI. The calculation results of RI of matrices of various orders are shown in the following table.

[0081] Table 2 Standard values ​​of random consistency indicators

[0082]

[0083] 3.3) The consistency deviation degree of the judgment matrix is ​​tested by the test coefficient CR. The specific calculation formula is:

[0084]

[0085] Generally, if CR<0.1, the consistency test is passed.

[0086] 4) After the consistency test is passed, the weight of each indicator element for the supercritical carbon dioxide Brayton cycle system is calculated, which is the total ranking:

[0087]

[0088] Embodiment 4 is:

[0089] On the basis of Example 1, the qualitative analysis of the efficiency of the supercritical carbon dioxide Brayton cycle system adopts a fuzzy comprehensive evaluation method.

[0090] In addition, the specific steps of the fuzzy comprehensive evaluation method are:

[0091] 1) Constructing evaluation factor dataset:

[0092] Suppose there is a set of k samples:

[0093] X={x 1 ,x 2 ,...,x k};

[0094] The characteristics of the pth sample are represented by h indicator eigenvalues:

[0095] x p =(x p1 ,x p2 ,...,x ph ) T ;

[0096] Then the sample can be represented as a k×h matrix:

[0097] X=(x pq );

[0098] Where: x pq is the value of index q of sample p; p = 1, 2, …, k; q = 1, 2, …, h.

[0099] 2) Constructing a review set: The present invention divides the reviews into five levels, namely {very good, good, average, very bad, poor}.

[0100] 3) Calculate the index membership: The membership refers to the relationship between a certain index and the set of comments in the performance evaluation of the supercritical carbon dioxide Brayton cycle system.

[0101] Specifically, for the fuzzy concept of supercritical carbon dioxide Brayton cycle system efficiency, the index characteristic u is set, and the relative membership of the index characteristic value u to attraction and repulsion is and The relative difference is:

[0102]

[0103] Then the evaluation index characteristic value u constitutes the attraction domain, repulsion domain and gradual qualitative change boundary of the evaluation index characteristic value set respectively:

[0104]

[0105] The variable factors of the evaluation index eigenvalue set include the variable model C A , variable parameters C B and other variable factors C C , then the attraction domain and repulsion domain of the variable factor set and C are:

[0106]

[0107] The quantitative variation domain of the variable factor set C is:

[0108]

[0109] One specific implementation is as follows: Figure 3 As shown in the figure, if [a, b] is the attraction domain of the evaluation index feature value set, [c, d] is a certain upper and lower bound range domain containing the attraction domain, and M is the attraction domain interval [a, b] points, then [c,a] and [b,d] are both exclusion domains of the eigenvalue set of the evaluation index.

[0110] x is any point in the range. When x is to the left of point M, the relative difference function is:

[0111]

[0112] When x is to the right of point M, the relative difference function is:

[0113]

[0114] Where: z is a non-negative exponent, which usually takes the value of 1, that is, the relative difference function model is a linear function; After determination, the relative membership can be solved

[0115] 4) Determine the fuzzy matrix: After completing the calculation of the membership degree of each indicator to each comment, the fuzzy matrix can be constructed.

[0116] The sample set is identified based on the standard eigenvalues ​​of the indicators at t levels according to the h indicators, and there is an h×s-order standard eigenvalue matrix of indicators:

[0117] Y=(y qs )(13)

[0118] Where: y qsis the s-level standard characteristic value of the q indicator, s=1,2,…,t.

[0119] Correspondingly, the attraction domain matrix and range domain matrix are:

[0120] I ab =([a qs ,b qs ]); (14)

[0121] I cd =([c qs ,d qs ]); (15)

[0122] Determine the attraction domain [a qs ,b qs ]middle Point value M qs The matrix:

[0123] M=(M qs ); (16)

[0124] By judging the position of the sample eigenvalue, the difference degree is completed using equations (10) to (11) Calculate, and then calculate the relative membership of the indicator to level s by formula (1) matrix:

[0125]

[0126] 5) Calculate the evaluation vector: In order to fully consider the weight of each indicator, the fuzzy operator of weighted evaluation is used for further evaluation, and then the evaluation vector can be obtained:

[0127]

[0128] Where: is the relative membership degree; n is the optimization criterion parameter; w q is the weight; h is the number of identification indicators; m is the distance parameter, and this paper assumes that m=1.

[0129] The relative membership matrix can be obtained from formula (18):

[0130] U'=( p u' s ); (19)

[0131] Normalize formula (19) to get the comprehensive relative membership matrix:

[0132] U=( p u s ); (20)

[0133]

[0134] 6) Calculate the efficiency of the supercritical carbon dioxide Brayton cycle system. According to the evaluation results of all the comments in the comment set, the assignment matrix P is obtained. The evaluation matrix and the assignment matrix are multiplied to obtain the efficiency evaluation result H of the supercritical carbon dioxide Brayton cycle system:

[0135] H=(1,2,...,t)·U; (22)

[0136] At this point, the quantitative and qualitative evaluation of the efficiency of the supercritical carbon dioxide Brayton cycle system can be achieved.

[0137] Combined with the review set constructed in step 2) and Figure 4 , give the corresponding comments and their corresponding score range.

[0138] The parts of the present invention that are not described in detail are prior art. It is obvious to those skilled in the art that the present invention is not limited to the details of the above-mentioned exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention; therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is limited by the appended claims rather than the above description. Therefore, it is intended to include all changes within the meaning and scope of the equivalent elements of the claims in the present invention, and any figure marks in the claims should not be regarded as limiting the claims involved.

Claims

1. A method for evaluating the performance of a supercritical carbon dioxide Brayton cycle system, characterized in that: Specific steps for: According to the evaluation indexes of supercritical carbon dioxide Brayton cycle system, an evaluation hierarchy model is established; Based on the various indicator elements and corresponding scales in the evaluation hierarchy model, a judgment matrix is ​​constructed; Calculate the weight of each indicator element in the judgment matrix and conduct a quantitative analysis of the efficiency of the supercritical carbon dioxide Brayton cycle system; Qualitative analysis of the performance of the supercritical carbon dioxide Brayton cycle system was conducted.

2. The method for evaluating the performance of a supercritical carbon dioxide Brayton cycle system according to claim 1, wherein: The evaluation hierarchy includes a system layer, an element layer and an indicator layer, wherein the system layer includes dedicated quality characteristics and general quality characteristics; The element layer of the dedicated quality characteristics includes energy saving, flexibility, compactness and economy; the index layer of energy saving includes energy conversion efficiency and compressed power consumption; the index layer of flexibility includes start-stop time and operating condition change rate; the index layer of compactness includes unit power volume; the index layer of economy includes specific power cost; The element layer of the general quality characteristics includes reliability, maintainability, safety, security, testability and environmental adaptability; the indicator layer of the reliability includes mean time before failure / failure, mean time between failures, mean time between serious failures, mean time between maintenance, service life, reliable life, storage life and first overhaul period; the indicator layer of the maintainability includes mean repair time, mean preventive maintenance time, important component replacement time and standardization rate; the indicator layer of the safety includes risk rate, accident rate and safety degree; the indicator layer of the security includes average security delay time, average management delay time, security equipment satisfaction rate, security equipment utilization rate, spare parts satisfaction rate and spare parts utilization rate; the indicator layer of the testability includes fault detection rate, fault isolation rate and false alarm rate; the indicator layer of the environmental adaptability includes natural environment adaptability and induced environment adaptability.

3. The method for evaluating the performance of a supercritical carbon dioxide Brayton cycle system as claimed in claim 2, wherein: The weight calculation of each indicator element in the judgment matrix adopts the hierarchical analysis method.

4. The method for evaluating the performance of a supercritical carbon dioxide Brayton cycle system as claimed in claim 3, wherein: The specific steps of the hierarchical analysis method are: 1) Obtain the maximum eigenvalue λ of the judgment matrix and its corresponding eigenvector; 2) Normalize the feature vector to obtain the corresponding weight w; 3) Perform consistency check on the judgment matrix; 4) After the consistency test is passed, the weight of each indicator element for the supercritical carbon dioxide Brayton cycle system is calculated.

5. The method for evaluating the performance of a supercritical carbon dioxide Brayton cycle system as claimed in claim 4, characterized in that: The specific steps of the consistency check are: 3.1) Calculate the consistency index CI as: Where: λ is the maximum characteristic root of the judgment matrix; n is the order of the judgment matrix 3.2) The consistency index RI is introduced, and the calculation formula of RI is: 3.3) The consistency deviation degree of the judgment matrix is ​​tested by the test coefficient CR. The specific calculation formula is:

6. The method for evaluating the performance of a supercritical carbon dioxide Brayton cycle system as claimed in claim 4, characterized in that: The weight calculation formula of each index element for the supercritical carbon dioxide Brayton cycle system is:

7. The method for evaluating the performance of a supercritical carbon dioxide Brayton cycle system as claimed in claim 2, wherein: The qualitative analysis of the efficiency of the supercritical carbon dioxide Brayton cycle system adopts a fuzzy comprehensive evaluation method.

8. The method for evaluating the performance of a supercritical carbon dioxide Brayton cycle system as claimed in claim 7, wherein: The specific steps of the fuzzy comprehensive evaluation method are: 1) Construct evaluation factor data set; 2) Construct a review collection; 3) Calculate the index membership based on the comment set and the evaluation factor data set; 4) Determine the fuzzy matrix according to the membership value of the indicator; 5) Calculate the evaluation vector based on the fuzzy matrix; 6) Calculate the efficiency of the supercritical carbon dioxide Brayton cycle system.

9. The method for evaluating the performance of a supercritical carbon dioxide Brayton cycle system according to claim 8, wherein: The evaluation factor dataset E p ={E p,1 , E p,2 ,…,E p,q }, where p is the specific number of layers in the evaluation hierarchy model, and q is the number of indicators in that layer.

10. The method for evaluating the performance of a supercritical carbon dioxide Brayton cycle system according to claim 8, wherein: The review set is {very good, good, average, very bad, poor}.

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