CN113222461B - AHP-CRITIC-based offshore wind power booster station cooling system evaluation method - Google Patents
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Abstract
An evaluation method of a cooling system of an offshore wind power booster station based on AHP-CRITIC is used for constructing an evaluation system of the cooling system of the offshore wind power booster station; constructing a judgment matrix of the criterion layer by using an AHP method, performing consistency test, and then obtaining the weight of each evaluation index of the criterion layer; constructing a judgment matrix of the evaluation layer, performing consistency test, and calculating the weight of each evaluation index of the evaluation layer; constructing a judgment matrix of the scheme layer, performing consistency test, and calculating the weight of each evaluation index of the scheme layer; calculating the total hierarchical ranking values of the evaluation layer and the scheme layer under the AHP method; calculating the evaluation index weights of an evaluation layer and a scheme layer by using a CRITIC weighting method; combining an AHP and CRITIC weighting method to obtain the combination weight of the evaluation layer and the scheme layer, thereby obtaining the optimal offshore wind power booster station cooling system scheme and determining the importance ranking of each evaluation index according to the weight. The invention combines the AHP and CRITIC weighting methods and is applied to the selection of the cooling system of the offshore wind power booster station, thereby being beneficial to the practical application and selection of other cooling systems.
Description
Technical Field
The invention relates to the field of cooling systems of offshore wind power booster stations, in particular to an AHP-CRITIC-based evaluation method of a cooling system of an offshore wind power booster station.
Background
The installation scale of the offshore wind power in China is increasingly enlarged, and the offshore wind power booster station is the heart of the offshore wind power. In the operation process of the offshore wind power booster station, a large amount of heat can be emitted to the indoor by the indoor power distribution device and equipment of each electrical system, when the indoor temperature is too high, the equipment unit can trigger high-temperature alarm and stop, the safe operation of the electrical equipment and the service life of the electrical equipment are affected, and meanwhile, the temperature in the machine room is increased to cause damage to the health of operators. Therefore, the quality of the cooling system is a key for guaranteeing the stable operation of the offshore wind power booster station.
There is currently little data on quantitative assessment of parameters in cooling systems. Most studies typically use only a single index or qualitative analysis, and fail to provide an overall assessment result. The evaluation methods for the system are mainly classified into subjective evaluation methods and objective evaluation methods. Among them, AHP (analytic hierarchy process) is an evaluation tool developed in 1970 s. It integrates multiple independent factors into one comprehensive factor, simplifying the complexity of ranking. The analytic hierarchy process is also successfully applied to the aspects of risk assessment, economic assessment, energy production technology assessment, room air supply mode selection and the like. The CRITIC weighting method is an objective weight for comprehensively measuring indexes based on the contrast intensity of evaluation indexes and the conflict between indexes, utilizes the objective attribute of data to carry out scientific evaluation, and is widely applied to aspects of urban traffic, agriculture, environment, business evaluation and the like.
The Chinese patent of the invention with the application number of 202010165473.2 proposes a self-healing capacity assessment method for an urban distribution network, which carries out comprehensive assessment on different distribution network investment schemes to obtain an investment scheme with highest score for comprehensively improving the self-healing capacity and effect of the distribution network, and guides the construction and transformation of distribution automation according to the investment scheme. However, this evaluation method is subjectively heavy, and objective comparison of the data of each scheme is not considered. The Chinese patent of application number 202011305974.2 proposes a method for selecting key components of an intelligent electric energy meter, which deeply combines objective data weights, corrects the defect of dependence on subjective experience of an expert in the traditional method, can realize scientific selection of the key components and form a most preferred scheme, thereby realizing improvement of the overall performance of the intelligent electric energy meter. However, the method does not consider the preference degree of a decision maker for the subjective evaluation method and the objective evaluation method.
Disclosure of Invention
The invention aims to solve the defects of the prior art, provides an evaluation method of a cooling system of an offshore wind power booster station based on AHP-CRITIC, combines a subjective evaluation method with an objective evaluation method, improves the defect that expert subjective experience is relied on in the traditional method, and simultaneously takes the preference degree of a decision maker for the subjective evaluation method and the objective evaluation method as a reference, so that the scientific selection of the scheme of the cooling system of the offshore wind power booster station can be realized, and the optimal scheme which is most suitable for the decision maker is formed.
An evaluation method of an offshore wind power booster station cooling system based on AHP-CRITIC comprises the following steps:
step one, constructing an evaluation system of a cooling system of the offshore wind power booster station, and dividing the evaluation system into four layers, namely a target layer, a criterion layer, an evaluation layer and a scheme layer;
constructing a judgment matrix of the criterion layer by using an AHP method, performing consistency test, and then obtaining the weight of each evaluation index of the criterion layer;
step three, constructing a judgment matrix of the evaluation layer, performing consistency test, and calculating the weight of each evaluation index of the evaluation layer;
step four, constructing a judgment matrix of the scheme layer, carrying out consistency test, and calculating the weight of each evaluation index of the scheme layer;
step five, calculating the evaluation index weights of an evaluation layer and a scheme layer under the AHP method;
step six, calculating the evaluation index weights of the evaluation layer and the scheme layer by using a CRITIC weighting method;
and step seven, combining an AHP and CRITIC weighting method to obtain the combination weight of the evaluation layer and the scheme layer, so that the optimal offshore wind power booster station cooling system scheme is obtained, and the importance ranking of each evaluation index can be determined according to the index weight of the evaluation layer.
Further, in the first step, in the constructed evaluation system of the cooling system of the offshore wind power booster station:
the target layer comprises the steps of selecting a cooling system scheme of the offshore wind power booster station;
the criterion layer comprises economy, construction and energy conservation;
the evaluation layer comprises equipment cost, manual installation cost, operation maintenance cost, scrapping and recycling, required space size, pipeline equipment installation difficulty, power consumption and renewable resource utilization rate;
the scheme layer comprises the scheme type of the cooling system to be selected.
Further, in the second step, the criterion layer has a judgment matrix of A 1 ＝(a ij ) n×n Wherein n is a judgment matrix A 1 The order of a) ij The ratio of the influence of any two indexes of economy, construction and energy conservation on the optimal selection of the cooling system of the target layer offshore wind power booster station is represented;
the formula for consistency test of the judgment matrix of the criterion layer is as follows:
wherein C is R Lambda is a satisfactory consistency index max R is the maximum eigenvalue of the matrix I The average random consistency index is valued and is related to the order n; c (C) R And if the consistency is less than 0.1, the consistency check is passed, the weight is determined, and if the consistency check is not passed, the adjustment judgment matrix is checked again.
Further, in the second step, the method for calculating the weight of each evaluation index of the criterion layer is as follows: calculating the maximum eigenvector of the criterion layer judgment matrix, and normalizing the maximum eigenvector to obtain each evaluation index weight matrix W a1 。
Further, in the third step, the judgment matrix of the evaluation layer is B m ＝(b kl ) p×p Wherein p is a judgment matrix B m The order of b kl The ratio of the influence of any two evaluation indexes to one evaluation index in the criterion layer in the associated evaluation indexes in the criterion layer is expressed.
Further, in the third step, the method for calculating the weight of each evaluation index of the evaluation layer is as follows: calculating the maximum eigenvector of the judgment matrix of the evaluation layer, and normalizing the maximum eigenvector to obtain each evaluation index weight matrix W '' am Evaluation layer each evaluationThe actual weights of the price indexes are: w (W) a2 ＝W a1 W’ am 。
Further, in the fourth step, the judgment matrix of the scheme layer is: c (C) y ＝(c rs ) t×t Wherein t is a judgment matrix C y The order of c rs The ratio of the influence of any two schemes on the evaluation index of the evaluation layer is shown for each evaluation index in the evaluation layer.
Further, the method for calculating the weight of each evaluation index of the scheme layer comprises the following steps: calculating the maximum eigenvector of the judgment matrix, and normalizing the maximum eigenvector to obtain index weight W' of each scheme for each evaluation index in the evaluation layer " ay The actual weights of the evaluation indexes of the scheme layer are as follows: w (W) a3 ＝W a2 W” ay 。
Further, the method for calculating the evaluation index weight of each layer by using the CRITIC weighting method comprises the following steps: firstly, listing scheme related original data, wherein the basis of an original data calculation method is expert scoring, statistical data and related standards, then carrying out dimensionless treatment on the original data, and carrying out forward treatment or reverse treatment on the data of each index; and calculating the quantization index of the variation between the jth index and other indexes, the correlation coefficient among the indexes, the quantization index of the conflict between the jth index and other indexes and the information quantity contained in the jth index, and finally calculating the weight of the jth index.
Further, the method for obtaining the combination weight of the evaluation layer and the scheme layer by combining the AHP and CRITIC weighting method comprises the following steps:
wherein the relative importance of the decision maker preference is theta, and 0 < theta < 1; q is the number of classes of weighting methods; the decision maker prefers the analytic hierarchy process to be lambda 1 ，0＜λ 1 < 1; preference of CRITIC weighting method is lambda 2 ，0＜λ 2 < 1, and lambda 1 +λ 2 ＝1；W (z) For a certain empowered partyThe evaluation index weight under the method; since there are only two weighting methods, the weighting method is consistent with coefficient beta 1 ＝β 2 ＝0.5。
The invention has the advantages and beneficial effects that:
according to the evaluation method of the cooling system of the offshore wind power booster station based on AHP-CRITIC, the subjective experience and objective index data of an expert are combined, an evaluation system of the cooling system of the offshore wind power booster station is constructed, importance of all evaluation indexes is ordered, and selection of the cooling system of the offshore wind power booster station is more scientific and effective. The whole quality of the cooling system of the offshore wind power booster station can be improved as a result of the selection, and the safe operation of the offshore wind power booster station is ensured. The AHP and CRITIC weighting method are combined and applied to the selection of the cooling system of the offshore wind power booster station, and the evaluation system is beneficial to the practical application and selection of other cooling systems.
Drawings
FIG. 1 is an evaluation system of a cooling system of an offshore wind power booster station in an embodiment of the invention.
FIG. 2 is an evaluation flow of a cooling system of an offshore wind farm booster station in an embodiment of the invention.
Detailed Description
The technical scheme of the invention is further described in detail below with reference to the attached drawings.
The invention relates to an evaluation method of an offshore wind power booster station cooling system based on AHP-CRITIC, which is further described by combining with the accompanying drawings and embodiments:
1. AHP analytic hierarchy process
The AHP calculates the basic step of index weight:
(1) The evaluation index system of the cooling system of the offshore wind power booster station is constructed, as shown in figure 1. The index system is divided into a target layer, a criterion layer, an evaluation layer and a scheme layer. The target layer comprises: optimal selection of a cooling system of the offshore wind power booster station; the criterion layer comprises: economy, construction and energy conservation; the evaluation layer comprises: equipment cost, manual installation cost, operation and maintenance cost, scrapping and recycling, required space size, pipeline equipment installation difficulty, power consumption and renewable resource utilization rate; the scheme layer comprises: the multi-split cooling system adopts a scheme 1, a fan coil cooling system adopting seawater as a cold source adopts a scheme 2, and a radiation cooling system adopting seawater as a cold source adopts a scheme 3.
(2) The method comprises the steps of constructing a judgment matrix, calculating the importance of all nodes related to the node of the upper layer according to the judgment matrix, and constructing a judgment matrix of a criterion layer to a target layer, a judgment matrix of an evaluation layer to the criterion layer and a plurality of judgment matrices of a scheme layer to the evaluation layer. With the uniform matrix method, not all factors are put together for comparison, but two by two. The relative scale is adopted during comparison, so that the difficulty of comparing different factors with each other in properties is reduced as much as possible, and the accuracy is improved. The index scoring criteria are shown in table 1.
Table 1 index scoring criteria
(3) And calculating the maximum eigenvector of the judgment matrix, and normalizing the maximum eigenvector to obtain a weight matrix W.
(4) Consistency test is carried out on the matrix:
wherein C is R Lambda is a satisfactory consistency index max Is the maximum eigenvalue of the matrix, n is the order, R I Take the value of the average random consistency index, C R And < 0.1, the consistency test is passed, and the weight is determined. The average random uniformity index values of the 1-8 orders are shown in Table 2.
Table 2 1-8 order average random uniformity index values
And constructing a judgment matrix according to the experience of an expert with knowledge of the offshore wind power booster station at 6 bits, and carrying out consistency test, as shown in table 3. The index weight matrix of each layer is shown in table 4.
Table 3 AHP weight calculation table
TABLE 4 AHP Entries weight summary table
In Table 4, in the criterion layer, the weights of economy, construction and energy conservation are directly obtained by the judgment matrix among the three indexes; in the evaluation layer, the inter-index weight is available from a judgment matrix formed between the indexes connected with the inter-index weight in the evaluation layer for one index in the criterion layer; in the evaluation layer, the actual weight is obtained by multiplying the weight among indexes by the index weight of the criterion layer connected with the index; in the scheme layer, each scheme weight is obtained by each scheme judgment matrix under the index of each evaluation layer; the total weight of each scheme is obtained by multiplying the weight of the scheme under each index of the evaluation layer by the sum of the actual weights of the evaluation layer.
2. CRITIC weighting method
The method comprises the following specific steps:
(1) Listing scheme related original data (total score of 10 points), wherein the basis of an original data calculation method is expert scoring, statistical data and related standards, as shown in table 5, performing dimensionless processing on the original data, and performing forward or reverse processing on the data of each index;
the larger the value of the index used, the better (forward index):
the smaller the value of the index used, the better (reverse index):
(2) Calculating a quantization index of variation of the j-th index and other indexes:
S j represents the standard deviation of j indexes.
(3) Calculating a correlation coefficient between the indexes:
where Cov (x, y) is the covariance between the indices x and y, var [ x ] is the variance of x, and Var [ y ] is the variance of y.
(4) Calculating a quantization index of the conflict between the j index and other indexes:
(5) Calculating the information amount contained in the j-th index:
(6) The weight of the j-th index is calculated as shown in table 6:
table 5 scheme related raw data
TABLE 6CRITIC weighting method evaluation layer index weight
3. Combined weighting
The combination weighting method combines subjective and objective conditions, calculates the index combination weight of an evaluation layer and the combination weight of each scheme, wherein the combination weight is as follows:
wherein the relative importance of the decision maker preference is theta, and 0 < theta < 1; q is the number of classes of weighting methods, q=2, and θ=0.56 is taken for the subject of evaluation; the decision maker prefers the analytic hierarchy process to be lambda 1 =0.7, preference for CRITIC weighting is λ 2 =0.3; since there are only two weighting methods, the weighting method consistency coefficient beta obtained by Spearman rank correlation coefficient 1 ＝β 2 ＝0.5。
The evaluation layer index combination weight and the individual scheme combination weight calculation results are shown in tables 7 and 8. In CRITIC weighting, each scheme weight is obtained by multiplying a judgment matrix by a weight coefficient.
Table 7 evaluation layer index combining weights
Table 8 weights of the schemes
4. Evaluation results
The radiation cooling system taking seawater as a cold source is superior to the multi-split cooling system and the fan coil cooling system taking seawater as the cold source through calculation. If the space is required to be saved, a radiation cooling system taking seawater as a cooling source is recommended to be selected; if the prior economic expenditure needs to be saved, suggesting to select a multi-split cooling system; if long-term economic expenditure is considered, a fan coil cooling system using seawater as a cold source or a radiation cooling system using seawater as a cold source is recommended.
The above description is merely of preferred embodiments of the present invention, and the scope of the present invention is not limited to the above embodiments, but all equivalent modifications or variations according to the present disclosure will be within the scope of the claims.
Claims (10)
1. An evaluation method of an offshore wind power booster station cooling system based on AHP-CRITIC is characterized by comprising the following steps: the method comprises the following steps:
step one, constructing an evaluation system of a cooling system of the offshore wind power booster station, and dividing the evaluation system into four layers, namely a target layer, a criterion layer, an evaluation layer and a scheme layer;
constructing a judgment matrix of the criterion layer by using an AHP method, performing consistency test, and then obtaining the weight of each evaluation index of the criterion layer;
step three, constructing a judgment matrix of the evaluation layer, performing consistency test, and calculating the weight of each evaluation index of the evaluation layer;
step four, constructing a judgment matrix of the scheme layer, carrying out consistency test, and calculating the weight of each evaluation index of the scheme layer;
step five, calculating the evaluation index weights of an evaluation layer and a scheme layer under the AHP method;
step six, calculating the evaluation index weights of the evaluation layer and the scheme layer by using a CRITIC weighting method;
and step seven, combining an AHP and CRITIC weighting method to obtain the combination weight of the evaluation layer and the scheme layer, so that the optimal offshore wind power booster station cooling system scheme is obtained, and the importance ranking of each evaluation index can be determined according to the index weight of the evaluation layer.
2. The AHP-CRITIC-based offshore wind power booster station cooling system evaluation method of claim 1, wherein the method comprises the steps of: step one, in a constructed evaluation system of a cooling system of the offshore wind power booster station:
the target layer comprises the steps of selecting a cooling system scheme of the offshore wind power booster station;
the criterion layer comprises economy, construction and energy conservation;
the evaluation layer comprises equipment cost, manual installation cost, operation maintenance cost, scrapping and recycling, required space size, pipeline equipment installation difficulty, power consumption and renewable resource utilization rate;
the scheme layer comprises the scheme type of the cooling system to be selected.
3. The AHP-CRITIC-based offshore wind power booster station cooling system evaluation method of claim 1, wherein the method comprises the steps of: in the second step, the judgment matrix of the criterion layer is A 1 ＝(a ij ) n×n Wherein n is a judgment matrix A 1 The order of a) ij The ratio of the influence of any two indexes of economy, construction and energy conservation on the optimal selection of the cooling system of the target layer offshore wind power booster station is represented;
the formula for consistency test of the judgment matrix of the criterion layer is as follows:
wherein C is R Lambda is a satisfactory consistency index max R is the maximum eigenvalue of the matrix I The average random consistency index is valued and is related to the order n; c (C) R And if the consistency is less than 0.1, the consistency check is passed, the weight is determined, and if the consistency check is not passed, the adjustment judgment matrix is checked again.
4. The AHP-CRITIC-based offshore wind power booster station cooling system evaluation method of claim 1, wherein the method comprises the steps of: in the second step, the method for calculating the weight of each evaluation index of the criterion layer is as follows: calculating the maximum eigenvector of the criterion layer judgment matrix, and normalizing the maximum eigenvector to obtain each evaluation index weight matrix W a1 。
5. The AHP-CRITIC-based offshore wind power booster station cooling system evaluation method of claim 1, wherein the method comprises the steps of: in the third step, the judgment matrix of the evaluation layer is B m ＝(b kl ) p×p Wherein p is a judgment matrix B m The order of b kl The ratio of the influence of any two evaluation indexes to one evaluation index in the criterion layer in the associated evaluation indexes in the criterion layer is expressed.
6. The AHP-CRITIC-based offshore wind power booster station cooling system evaluation method of claim 1, wherein the method comprises the steps of: in the third step, the method for calculating the weight of each evaluation index of the evaluation layer comprises the following steps: calculating the maximum eigenvector of the judgment matrix of the evaluation layer, and normalizing the maximum eigenvector to obtain each evaluation index weight matrix W '' am The actual weights of the evaluation indexes of the evaluation layer are as follows: w (W) a2 ＝W a1 W’ am 。
7. The AHP-CRITIC-based offshore wind power booster station cooling system evaluation method of claim 1, wherein the method comprises the steps of: in the fourth step, the judgment matrix of the scheme layer is: c (C) y ＝(c rs ) t×t Wherein t is a judgment matrix C y The order of c rs The ratio of the influence of any two schemes on the evaluation index of the evaluation layer is shown for each evaluation index in the evaluation layer.
8. The AHP-CRITIC-based offshore wind power booster station cooling system evaluation method of claim 1, wherein the method comprises the steps of: the method for calculating the weight of each evaluation index of the scheme layer comprises the following steps: calculating the maximum eigenvector of the judgment matrix, and normalizing the maximum eigenvector to obtain index weight W' of each scheme for each evaluation index in the evaluation layer " ay The actual weights of the evaluation indexes of the scheme layer are as follows: w (W) a3 ＝W a2 W” ay 。
9. The AHP-CRITIC-based offshore wind power booster station cooling system evaluation method of claim 1, wherein the method comprises the steps of: the method for calculating the evaluation index weight of each layer by using the CRITIC weighting method comprises the following steps: firstly, listing scheme related original data, wherein the basis of an original data calculation method is expert scoring, statistical data and related standards, then carrying out dimensionless treatment on the original data, and carrying out forward treatment or reverse treatment on the data of each index; and calculating the quantization index of the variation between the jth index and other indexes, the correlation coefficient among the indexes, the quantization index of the conflict between the jth index and other indexes and the information quantity contained in the jth index, and finally calculating the weight of the jth index.
10. The AHP-CRITIC-based offshore wind power booster station cooling system evaluation method of claim 1, wherein the method comprises the steps of: combining AHP and CRITIC weighting methods, the method for obtaining the combination weights of the evaluation layer and the scheme layer is as follows:
where the relative importance of the decision maker preference is θ,θ is more than 0 and less than 1; q is the number of classes of weighting methods; the decision maker prefers the analytic hierarchy process to be lambda 1 ，0＜λ 1 < 1; preference of CRITIC weighting method is lambda 2 ，0＜λ 2 < 1, and lambda 1 +λ 2 ＝1；W (z) The evaluation index weight is given to a certain weighting method; since there are only two weighting methods, the weighting method is consistent with coefficient beta 1 ＝β 2 ＝0.5。
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| CN111523795A (en) * | 2020-04-21 | 2020-08-11 | 西南石油大学 | Method for evaluating damage of shallow natural gas in region containing oil-gas basin to tunnel |
| CN111563682A (en) * | 2020-05-07 | 2020-08-21 | 贵州电网有限责任公司 | Test evaluation method for distribution automation equipment |
| CN111859680A (en) * | 2020-07-24 | 2020-10-30 | 武汉理工大学 | Comprehensive evaluation method for system performance |
| CN112365135A (en) * | 2020-10-27 | 2021-02-12 | 西安热工研究院有限公司 | Fuzzy analytic hierarchy process based wind power blade manufacturing quality evaluation method, system and equipment |
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