Site selection suitability evaluation method for marine ranch and offshore wind power fusion construction based on combination of analytic hierarchy process and entropy weight method

Abstract

The invention discloses a marine ranch and offshore wind power fusion construction site selection suitability evaluation method based on combination of analytic hierarchy process and entropy weight method, and the method aims at the site selection comprehensive evaluation of marine ranch and offshore wind power fusion construction based on a comprehensive evaluation index system, and improves the site selection suitability of marine ranch and offshore wind power fusion construction through hierarchical and systematic analysis. An evaluation target and a criterion layer are clarified by comprehensively considering multiple dimensions of a geological environment, a meteorological and hydrological environment, an accident risk, a biological environment and a navigation environment, the weight of an evaluation index system is determined, the information amount of each index is quantized by using an entropy weight method, and an objective basis is provided for decision making.

Description

Technical Field

[0001] The present invention belongs to the technical field of offshore wind power, and particularly relates to a method for evaluating the site suitability of the integrated construction of ocean ranch and offshore wind power based on the combination of analytic hierarchy process and entropy weight method. Technical Background

[0002] With the continuous growth of the global demand for clean energy, offshore wind power, as a form of renewable energy, has received increasing attention. At the same time, ocean ranch has also become one of the important means for marine ecological protection and sustainable utilization of fishery resources. Integrating the construction of ocean ranch and offshore wind power can realize the comprehensive utilization of marine resources, improve the utilization rate of marine space and economic benefits. However, due to the complexity and uncertainty of the marine environment, how to select a suitable site is crucial for the success of the integrated construction.

[0003] The existing technologies mainly focus on site selection methods based on single indicators or simple multi-indicators. These methods usually only consider one or a few factors, such as wind resources, water depth, distance from the shoreline, etc., while ignoring other important environmental and social factors. For example, some methods may only focus on the abundance of wind resources, or overly focus on water quality indicators, while ignoring factors such as geological stability, biodiversity protection, and fishery resource distribution. In addition, traditional single analysis methods have disadvantages such as strong subjectivity, lack of objective data support, complex consistency test, difficulty in processing large amounts of data, and ignoring the internal structure of data in the evaluation of site suitability.

[0004] The advantage of the present invention lies in that through multi-criteria decision analysis based on the analytic hierarchy process, complex problems can be decomposed into multiple levels, and decisions can be made by comparing the importance between different levels. The present invention can construct a comprehensive evaluation index system, and through hierarchical and systematic analysis, by comprehensively considering multiple dimensions such as geological environment, meteorological and hydrological environment, accident risk, biological environment, and navigation environment, the comprehensiveness and scientificity of the evaluation are improved. Because the analytic hierarchy process can more scientifically determine the weights of each index through pairwise comparison and consistency test, reduce subjective deviation, and conduct analysis based on data-driven, while the TOPSIS entropy weight method can measure the degree of data dispersion by calculating information entropy, thus being able to better reflect the internal structure and differences of data. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for evaluating the site suitability of the integrated construction of ocean ranch and offshore wind power based on the analytic hierarchy process and TOPSIS entropy weight method. Aiming at the problem that the existing site selection methods are difficult to take into account the multiple needs of ocean ranch and offshore wind farm, and the evaluation process lacks quantification and systematization, through the combination of the analytic hierarchy process and TOPSIS entropy weight method, a scientific, reasonable and efficient evaluation means is provided for decision-makers.

[0006] To achieve the above object, the technical solution of the present invention is as follows: A method for evaluating the site suitability of the integrated construction of ocean ranch and offshore wind power based on the analytic hierarchy process and TOPSIS entropy weight method, comprising the following steps:

[0007] Step S1. Construct a hierarchical structure model to determine the target layer, criterion layer, and scheme layer for the integrated construction site selection of ocean ranch and offshore wind power;

[0008] Step S2. Construct an evaluation index system. On the basis of the criterion layer, refine and construct the sub-criterion layer, obtain information and collect data, and construct a judgment matrix;

[0009] Step S3. Conduct a consistency test on the judgment matrix;

[0010] Step S4. Calculate the weights of each index. Using the judgment matrix that has passed the consistency test, calculate the weights of each evaluation index;

[0011] Step S5. According to the characteristics and requirements of the integrated construction of ocean ranch and offshore wind power, perform normalization and quantification processing on the elements of the sub-criterion layer;

[0012] Step S6. Organize the quantified data according to the hierarchical structure model and evaluation index system, and combine the weights of each index. Calculate the comprehensive evaluation value of each site selection scheme by the weighted linear combination method;

[0013] Step S7. According to the output comprehensive evaluation value, comprehensively evaluate the site suitability of the integrated construction of ocean ranch and offshore wind power;

[0014] In the above S1, the hierarchical structure model consists of three main levels, which are, from the upper layer to the lower layer, the highest layer, the middle layer, and the bottom layer; among them, the highest layer is the target layer, that is, the evaluation of the site suitability of the integrated construction of ocean ranch and offshore wind power for different schemes; the middle layer is the criterion layer, which is composed of the criterion layer (Ma) and the sub-criterion layer (Mi). Among them, the elements of the criterion layer are geological environment (A), meteorological and hydrological environment (B), accident risk (C), biological environment (D), and navigation environment (E); the bottom layer is the scheme layer;

[0015] In the above S1, the sub-criteria included in the geological environment (A) of the criterion layer of the hierarchical structure model are: a1 net bearing capacity of the seabed surface, a2 geological structure; the sub-criteria included in the meteorological and hydrological environment (B) of the criterion layer are: b1 average wind speed, b2 average surface horizontal flow velocity during the spring tide period; the sub-criteria included in the accident risk (C) of the criterion layer are: c1 oil spill risk (sweeping area in 72 hours); the sub-criteria included in the biological environment (D) of the criterion layer are: d1 absolute resource density of nekton, d2 species diversity index; the sub-criteria included in the navigation environment (E) of the criterion layer are: e1 distance to the nearest waterway;

[0016] In S2, the pairwise comparison method is used to compare the elements in the criterion layer, and the following principles are followed in the process of constructing the judgment matrix:

[0017] When element i and element j are equally important to the upper-level factor, a ij = 1;

[0018] When element i is slightly more important than element j, a ij = 3;

[0019] When element i is more important than element j, a ij = 5;

[0020] When element i is much more important than element j, a ij = 7;

[0021] When element i is extremely more important than element j, a ij = 9;

[0022] When the importance of element i and element j is between a ij = 2n–1 and a ij = 2n+1, a ij = 2n, n = 1, 2, 3, 4;

[0023] When n = 1, 2, …, 9, and if and only if a ij = n, a ji = 1 / n;

[0024] In S3, the consistency test is the comparison process of the consistency ratio R C with the standard value of 0.1. If R C > 0.1, the consistency test is not passed and the judgment matrix needs to be reconstructed. If R C < 0.1, the consistency test is passed and subsequent processing can be carried out. It is judged according to the following formula:

[0025]

[0026] where λ max is the maximum eigenvalue of the judgment matrix; I C is the consistency index (used to measure the degree of deviation of the judgment matrix from consistency); n is the matrix dimension; R C is the consistency ratio; I R is the random index of the n-order matrix, and the value can be referred to Table 1:

[0027] Table 1

[0028]

[0029] In S4, the weights of the judgment matrix can be obtained by using the geometric mean method, the eigenvalue method, and the least squares method;

[0030] In S5, all evaluation criteria are normalized by combining the dualism method, the assignment method, and the membership function method; among them, the membership function includes three types, namely S-type, trapezoidal, and Z-type membership functions, and its normalization range is 0 to 1, where 0 represents the lowest suitability and 1 represents the highest suitability.

[0031] For the sub-criterion containing the element a2 geological structure, the assignment method is used for normalization processing. According to the qualitative element evaluation, sorting is carried out, and the qualitative elements in different schemes are assigned values of 1, 2, 3,... from poor to good in turn. If the evaluation performances of two schemes are the same, the assigned values are the same;

[0032] After the assignment is completed, the following formula is used for normalization processing of this element:

[0033]

[0034] Among them, X is the element assignment in each scheme;

[0035] For the sub-criterion elements a1 net bearing capacity of the seabed surface, c1 oil spill risk (sweeping area in 72 hours), d1 absolute resource density of nekton, d2 species diversity index, and e1 distance to the nearest shipping lane, the dualism method is used for normalization processing. If the element is a positive index, the following formula is used for normalization processing:

[0036]

[0037] If the element is a negative index, the following formula is used for normalization processing:

[0038]

[0039] Among them, X is the actual measured value, X min The minimum actual measured value in the parallel scheme, X max The maximum actual measured value in the parallel scheme;

[0040] For the sub-criterion element b1 average wind speed, the S-type membership function method is used for normalization processing, and the following formula is used for normalization processing:

[0041]

[0042] Among them, S is the membership degree corresponding to each measured value, K1 and K2 are characteristic parameters, X is the actual measured value, and a, b, c, and d are the division thresholds of the suitability intervals corresponding to each criterion;

[0043] The calculation method of the average surface horizontal velocity of the secondary criterion element b2 during the spring tide period using the trapezoidal membership function is normalized according to the following formula:

[0044]

[0045] Among them, S is the membership degree corresponding to each measurement value, K is the characteristic parameter, X is the actual measurement value, and a and b are the division thresholds of the suitability interval corresponding to each criterion;

[0046] In S6, a hierarchical structure model is constructed, and the weighted linear combination method is used to calculate the suitability evaluation value R of each scheme ij :

[0047] R ij =W i S ij

[0048] Among them, S ij is the normalized value of the secondary criterion in each scheme, and W i is the weight value of the criterion to which the secondary criterion belongs.

[0049] In S7, the positive and negative ideal solutions of the indicators are the basis for subsequent evaluations. The closer the vector value of the indicator is to the positive ideal solution, the better its performance; the closer it is to the negative ideal solution, the worse its performance. The positive ideal solution is:

[0050] R + =max(R i1 ,R i2 ,R i3 )

[0051] The negative ideal solution is:

[0052] R - =min(R i1 ,R i2 ,R i3 )

[0053] In S8, calculate the Euclidean space distance of each evaluation object to the positive ideal solution and the negative ideal solution:

[0054]

[0055] In S9, calculate the comprehensive evaluation value C of each scheme:

[0056]

[0057] According to the comprehensive evaluation value C of each scheme, compare the siting suitability of the integrated construction of offshore pastures and offshore wind farms for each scheme. Description of the Drawings

[0058] Figure 1It is a flowchart of a method for evaluating the siting suitability of the integrated construction of an ocean ranch and an offshore wind farm based on the analytic hierarchy process and the TOPSIS entropy weight method according to the present invention;

[0059] Figure 2 It is a hierarchical structure model of a method for evaluating the siting suitability of the integrated construction of an ocean ranch and an offshore wind farm based on the analytic hierarchy process and the TOPSIS entropy weight method according to the present invention. Specific implementation manners

[0060] The technical solutions of the present invention and the effects produced thereby will be clearly and detailedly described below in combination with embodiments and the accompanying drawings to fully understand the objectives, solutions and effects of the present invention. This embodiment is implemented based on the technical solutions of the present invention, and specific implementation manners and detailed operation processes are given, but the protection scope of the present invention is not limited to the following embodiments.

[0061] As Figure 1 shown is a flowchart of a method for evaluating the siting suitability of the integrated construction of an ocean ranch and an offshore wind farm based on the analytic hierarchy process according to the present invention. The following will be combined with Figure 1 to elaborate on a method for evaluating the siting suitability of the integrated construction of an ocean ranch and an offshore wind farm based on the analytic hierarchy process implemented according to the present invention:

[0062] The following descriptions respectively select three functional sea areas, namely, the sea area between the Laizhou New Energy Mineral and Energy Area and the Laizhou Bay Aquaculture and Fishery Area in the Laizhou Bay, the Laizhou Taipingwan Aquaculture and Fishery Area, and the Laizhou Tourism and Recreation Area, as Case 1, Case 2, and Case 3 of the basic embodiment, and evaluate the construction benefits on the premise of the technical solutions of the present invention;

[0063] An embodiment of the present invention provides a method for evaluating the siting suitability of the integrated construction of an ocean ranch and an offshore wind farm based on the analytic hierarchy process, specifically including the following steps:

[0064] 1. Construct a hierarchical structure model as Figure 2As shown in the figure, from the upper layer to the lower layer are the top layer, the middle layer, and the bottom layer in sequence; among them, the top layer is the target layer, that is, the siting suitability assessment for the integrated construction of different marine ranching and offshore wind power projects; the middle layer is the criterion layer, which consists of the criterion layer (Ma) and the sub-criterion layer (Mi). Among them, the constituent elements of the criterion layer are geological environment (A), meteorological and hydrological conditions (B), accident risk (C), biological environment (D), and navigation environment (E); among them, the sub-criterion layer under the geological structure of the criterion layer includes elements: a1 net bearing capacity of the seabed surface, a2 geological structure; the sub-criterion layer under the meteorological and hydrological conditions of the criterion layer includes elements: b1 average wind speed, b2 average surface horizontal flow velocity during the spring tide period; the sub-criterion layer under the accident risk of the criterion layer includes elements: c1 oil spill risk (sweeping area in 72 hours); the sub-criterion layer under the biological environment of the criterion layer includes elements: d1 absolute resource density of nekton, d2 species diversity index; the sub-criterion layer under the navigation environment of the criterion layer includes elements: e1 distance to the nearest shipping lane;

[0065] 2. Use the pairwise comparison method to compare the elements of the criterion layer and construct the judgment matrix as follows:

[0066]

[0067]

[0068] 3. According to the method for siting suitability assessment of the integrated construction of marine ranching and offshore wind power based on the analytic hierarchy process described in claim 1, it is characterized in that in S3, the consistency test is the comparison process between the consistency ratio and the standard value of 0.1, and it is judged according to the following formula:

[0069]

[0070] Among them, λ max is the maximum eigenvalue of the judgment matrix, n is the matrix dimension, R C is the consistency ratio, and I R is the random index of the n-order matrix;

[0071] According to the judgment matrix, it can be known that λ max = 5.24, so I C = 0.06; the random index I R of the order matrix refers to Table 1, and the consistency index R C corresponding to the judgment matrix = 0.05 < 0.1, indicating that the consistency of the judgment matrix is good. Finally, the weights of the elements of the criterion layer (Ma) are calculated as follows:

[0072] A = 0.5;

[0073] B = 0.26;

[0074] C = 0.07;

[0075] D = 0.13;

[0076] E = 0.03;

[0077] 4. Quantify the secondary criterion elements. The secondary criterion includes element a2 geological structure. Use the assignment method for normalization. Sort according to the element characteristics evaluation. Assign values of 1, 2, 3, …, n to the qualitative elements in the plan from poor to good. If the evaluation performances of two plans are the same, assign the same value;

[0078] According to the geological surveys of the three target areas in the Laizhou Bay, both the Laizhou New Energy Minerals and Energy Area and the Laizhou Bay Agriculture and Fishery Area in the Laizhou Bay are clayey silty bottoms, and both the Laizhou Taipingwan Agriculture and Fishery Area and the Laizhou Tourism and Recreation Area are muddy bottoms;

[0079] Compared with the muddy bottom, the clayey silty bottom usually has better bearing capacity, can provide a more solid foundation support for wind turbines, and reduce the risks of settlement and inclination. Secondly, the lower permeability can reduce water penetration and potential formation instability problems, and the higher friction coefficient helps to increase the friction between the wind turbine and the bottom, enhancing stability. Construction may also be more convenient, facilitating foundation construction. Therefore, assign a value of 2 to the geological structure of Plan 1, and assign a value of 1 to the geological structures of Plan 2 and Plan 3, and perform normalization on them

[0080]

[0081]

[0082] 5. Use the binary method for normalization of the seabed surface net bearing capacity, oil spill risk (72-hour sea sweeping area), absolute resource density of nekton, species diversity index, and the closest distance to the roadway in the secondary criterion elements. Take d1 absolute resource density of nekton and c1 oil spill risk (72-hour sea sweeping area) as examples:

[0083] According to the latest fishery resource survey data of Plan 1, Plan 2, and Plan 3, the absolute resource densities of nekton for the three plans are 276.58 kg / km 2 、44.69 kg / km 2 、49.32 kg / km 2 , and the absolute resource density of nekton is a positive indicator. Normalize the absolute resource densities of nekton for the three plans and substitute them into the formula:

[0084]

[0085] Therefore, the normalized quantification results of the absolute resource densities of nekton for the three plans are: [1, 0, 0.02];

[0086] Calculated based on the oil spill prediction analysis of three scenarios for the oil film diffusion range 72 hours later, the oil film diffusion ranges of Scenario 1, Scenario 2, and Scenario 3 72 hours later are 107.39 km 2 , 129.92 km 2 , 113.25 km 2 , and the oil spill change is a negative indicator. The oil spill risks of the three scenarios are normalized and substituted into the formula:

[0087]

[0088] Therefore, the normalized quantitative results of the oil spill risks of the three scenarios are: [1, 0, 0.02];

[0089] 6. The average wind speed of the secondary criterion element b1 is normalized using the S-shaped membership function method and processed according to the following formula:

[0090]

[0091] For the pre-construction of offshore wind power, the more suitable wind speed range is usually between 5 m / s and 25 m / s per second. Therefore, in the formula, a = 5, b = 25, K = 1. Through the wind condition statistics of the sea area, the average wind speeds of Scenario 1, Scenario 2, and Scenario 3 are 7.4 m / s, 5.1 m / s, and 6 m / s respectively. The normalized processing calculation of the average wind speeds of the three scenarios shows that: S1 = 0.12, S2 = 0.005, S3 = 0.05;

[0092] 7. The calculation method for the average surface horizontal velocity during the spring tide of the secondary criterion element b2 using the trapezoidal membership function is processed according to the following formula:

[0093]

[0094] In the formula, a = 0.2, b = 0.4, c = 0.6, d = 0.8, K1 = 1.32, K2 = 1.74. Based on the observation of the measured sea current characteristic values of the sea area, the average surface horizontal velocities during the spring tide of Scenario 1, Scenario 2, and Scenario 3 are 0.48 m / s, 0.39 m / s, and 0.44 m / s respectively. The normalized processing calculation of the average surface horizontal velocities during the spring tide of the three scenarios shows that: S1 = 1, S2 = 0.93, S3 = 1;

[0095] 7. According to the normalized quantitative results, the hierarchical structure model is constructed as follows:

[0096]

[0097] e = [1 0.7 0];

[0098] 8. Using the weighted linear combination method: Rij = W i S ij Obtain the weighted matrix R ij :

[0099]

[0100] Obtain the positive ideal solution based on the normalized quantization result:

[0101] R + = (0.5, 0.25, 0.03, 0.26, 0.07, 0.13, 0.13, 0.03) T

[0102] Obtain the negative ideal solution:

[0103] R - = (0, 0.13, 0, 0.24, 0, 0, 0, 0) T

[0104] Euclidean space distance of the positive ideal solution: D + = (0, 0.4948, 0.5465)

[0105] Euclidean space distance of the negative ideal solution: D - = (0.5536, 0.0683, 0.0566)

[0106] The C values of the final calculated solutions 1, 2, and 3 are 1, 0.12, and 0.09 respectively;

[0107] 9. According to the output result of the model, the scoring result of solution 1 is 1, which is the largest, followed by the scoring result of solution 2 being 0.12, and finally the scoring result of solution 1 being 0.09. Therefore, it is most suitable to carry out the integrated construction of ocean ranch and offshore wind power at solution 1 (the sea area between the Laizhou New Energy Minerals and Energy Area and the Laizhou Bay Fishery and Aquaculture Area in the Laizhou Bay).

[0108] 10. In order to verify the effectiveness of a method for evaluating the site suitability of the integrated construction of ocean ranch and offshore wind power based on the analytic hierarchy process and TOPSIS entropy weight method involved in the present invention, the comprehensive scores of each solution calculated by the present invention are compared with those obtained by using the analytic hierarchy process alone and the TOPSIS entropy weight method alone:

[0109] ① In the present invention, the weight values of each criterion layer (Ma) have been calculated using the analytic hierarchy process:

[0110] A = 0.5;

[0111] B = 0.26;

[0112] C = 0.07;

[0113] D = 0.13;

[0114] E = 0.03;

[0115] According to the normalization results of the secondary criterion layer indicators:

[0116]

[0117] e = [1 0.7 0];

[0118] According to the weighted linear combination method:

[0119] C* = ΣWS j

[0120] The final scores C* values of Scheme 1, Scheme 2, and Scheme 3 obtained according to the analytic hierarchy process are 1.4, 1.04, and 0.43 respectively;

[0121] ② Using the TOPSIS entropy weight method, the information entropy value is calculated according to the data information of the secondary criterion layer (Mi): Entropy value = (0.323, 0, 0.541, 0.63, 0.621, 0.088, 0.174, 0.617)

[0122] And the information utility value:

[0123] Utility value = (0.677, 1, 0.459, 0.37, 0.379, 0.912, 0.826, 0.383)

[0124] The final calculated weight value W*:

[0125] W* = (0.135, 0.2, 0.092, 0.074, 0.076, 0.182, 0.165, 0.077)

[0126] Multiply the calculated weight by the standardized data, and calculate the Euclidean space distance D* of the positive ideal solution based on the obtained new weighted decision matrix + = (0.0272, 0.9475, 0.8800) and the Euclidean space distance of the negative ideal solution: D* - = (0.9929, 0.1993, 0.3605);

[0127] The final scores C** values of Scheme 1, Scheme 2, and Scheme 3 obtained according to the TOPSIS entropy weight method are 0.973, 0.174, and 0.291 respectively;

[0128] Therefore, the C values calculated by the three methods are:

[0129] C = (1, 0.12, 0.09)

[0130] C* = (1.4, 1.04, 0.43)

[0131] C** = (0.973, 0.174, 0.291)

[0132] To evaluate the site selection evaluation method for the integration of offshore pastures and offshore wind farms, it is necessary to determine the weight of the method used based on the degree of dispersion of the comprehensive scores of each plan calculated by different methods. Therefore, the TOPSIS entropy weight method is used to analyze the C values calculated by three methods, and the calculated comprehensive scores are as follows:

[0133] Analytic Hierarchy Process & TOPSIS Entropy Weight Method: 1

[0134] Analytic Hierarchy Process: 0.24

[0135] TOPSIS Entropy Weight Method: 0.08

[0136] Therefore, a site selection suitability evaluation method for the integration of offshore pastures and offshore wind farms based on the combination of the Analytic Hierarchy Process and the TOPSIS entropy weight method involved in the present invention has better evaluation accuracy than using the Analytic Hierarchy Process alone or the TOPSIS entropy weight method alone.

[0137] Although the description of the present invention has been quite detailed and particularly describes several of the described embodiments, it is not intended to be limited to any such details, embodiments or any particular embodiment, and thus effectively covers the intended scope of the present invention. The foregoing describes the present invention based on the embodiments foreseeable by the inventor in order to demonstrate the main characteristics and advantages of the present invention. In addition, various improvements may exist for the present invention, and these changes and improvements are all within the scope of the present invention claimed. The scope of protection of the present invention shall be defined by the appended claims.

Claims

1. A site suitability assessment method for the integrated construction of marine ranches and offshore wind power based on the combination of hierarchical analysis and entropy weight method, characterized in that: The following steps are involved: S1. Construct a hierarchical model to determine the target layer, criterion layer, and plan layer for the site selection of the integrated construction of marine ranches and offshore wind power; S2. Construct an evaluation index system. On the basis of the criterion layer, construct a sub-criterion layer, obtain information and collect data, and construct a judgment matrix; S3. Perform consistency check on the judgment matrix; S4. Calculate the weight of each indicator, and use the judgment matrix that passes the consistency test to calculate the weight of each evaluation indicator; S5. According to the characteristics and requirements of the integrated construction of marine ranches and offshore wind power, the sub-criteria layer elements are normalized and quantified; S6. Arrange the quantitative data according to the hierarchical structure model and evaluation index system, and combine the weights of each index to obtain the weighted standard matrix of the sub-level through the weighted linear combination method; S7. Determine the positive ideal solution and the negative ideal solution according to the weighted normative matrix; S8. Calculate the Euclidean space distance of each evaluation object to the positive ideal solution and the negative ideal solution; S9. Calculate the comprehensive evaluation value of each plan, and conduct a comprehensive assessment of the site suitability for the integrated construction of marine ranches and offshore wind power based on the output comprehensive evaluation value.

2. The method according to claim 1, characterized in that In step S1, the hierarchical model is composed of three main layers, which are the highest layer, the middle layer, and the lowest layer from the upper layer to the lower layer; the highest layer is the target layer, which evaluates the site suitability of the integrated construction of marine ranches and offshore wind power in different schemes; the middle layer is the criterion layer, which is composed of the criterion layer Ma and the sub-criterion layer Mi, wherein the constituent elements of the criterion layer are geological environment A, meteorological and hydrological environment B, accident risk C, biological environment D, and navigation environment E; the lowest layer is the scheme layer; In the hierarchical model, the sub-criteria under the geological environment A include element a1 net bearing capacity of the seabed surface and a2 geological structure; the sub-criteria under the meteorological and hydrological environment B include element b1 average wind speed and b2 average surface water velocity during high tide; the sub-criteria under the accident risk C include element c1 oil spill risk; the sub-criteria under the biological environment D include element d1 absolute resource density of swimming animals and d2 species diversity index; the sub-criteria under the navigation environment E include element e1 distance to the nearest waterway.

3. The method according to claim 1 or 2, characterized in that: In step S2, the elements of the criterion layer are compared using a pairwise comparison method, and the judgment matrix is ​​constructed in accordance with the following principles: When element i and element j are equally important to the factors at the previous level, a ij =1; When element i is slightly more important than element j, a ij =3; When element i is more important than element j, a ij =5; When element i is much more important than element j, a ij =7; When element i is more important than element j, a ij =9; When the importance of element i and element j is between a ij =2n–1 and a ij =2n+1, a ij =2n,n=1,2,3,4; When n=1,2,…,9, and if and only if a ij =n,a ji =1 / n.

4. The method according to claim 1 or 2, characterized in that: In step S3, the consistency check is the consistency ratio R C Compared with the standard value 0.1, if R C >0.1, the consistency test fails and the judgment matrix needs to be rebuilt. C <0.1, the consistency test is passed and subsequent processing can be performed according to the following formula: Among them, λ max is the maximum eigenvalue of the judgment matrix; n is the matrix dimension; R C is the consistency ratio; I R is the random index of the n-order matrix. When n is 1 to 6, I R The values ​​are 0.00, 0.00, 0.52, 0.89, 1.12, and 1.26; In step S4, the weights of the judgment matrix are calculated using the geometric mean method, the eigenvalue method and the least squares method.

5. The method according to claim 1 or 2, characterized in that: In step S5, all evaluation criteria are normalized by combining the dualism method, the assignment method and the membership function method; wherein the membership function includes three types, namely, the S-type and the ladder-type membership function, and the normalized range is 0 to 1, wherein 0 represents the lowest suitability and 1 represents the highest suitability.

6. The method according to claim 1 or 2, characterized in that: In step S5: (1) The secondary criteria include element a2 geological structure, which is normalized using the assignment method and ranked according to the qualitative element evaluation. The qualitative elements in different schemes are assigned values ​​of 1, 2, 3, ..., n from the worst to the best, and the assigned values ​​are the same; After the assignment is completed, the element is normalized using the following formula: Among them, X is the value assigned to the elements in each scheme; (2) The secondary criterion elements a1 net carrying capacity of the seabed surface, c1 oil spill risk, d1 absolute resource density of swimming animals, d2 species diversity index, and e1 distance to the nearest waterway are normalized using the dualism method. If the element is a positive indicator, it is normalized according to the following formula: If the element is a negative indicator, it is normalized according to the following formula: Among them, X is the actual measured value, X min The actual minimum value measured in the parallel scheme, X max The maximum value actually measured in the parallel scheme; (3) The average wind speed of the secondary criterion element b1 is normalized using the S-type membership function method according to the following formula: Among them, S is the membership degree corresponding to each measurement value, K1 and K2 are characteristic parameters, X is the actual measurement value, and a, b, c, and d are the division thresholds of the suitability interval corresponding to each criterion; (4) The secondary criterion element b2, the average surface water velocity during the high tide period, is calculated using a trapezoidal membership function and normalized according to the following formula: Among them, S is the membership degree corresponding to each measurement value, K is the characteristic parameter, X is the actual measurement value, and a and b are the division thresholds of the suitability interval corresponding to each criterion.

7. The method according to claim 1 or 2, characterized in that: In step S6, the hierarchical model is constructed by using the weighted linear combination method to obtain the sub-criteria weighted normative matrix R ij : R ij =W i S ij Among them, S ij is the normalized value of the subcriteria in each scheme, W i is the weight of the criterion to which the subcriteria belongs.

8. The method according to claim 7, characterized in that In step S7, the positive and negative ideal solutions of the indicator are the basis for subsequent evaluation. The closer the vector value of the indicator is to the positive ideal solution, the better its performance is, and the closer it is to the negative ideal solution, the worse its performance is. The positive ideal solution is: R + =max(R i1, R i2, R i3 ) The negative ideal type solution is: R - =min(R i1, R i2, R i3 ) 9. The method according to claim 8, characterized in that In step S8, the Euclidean space distance from each evaluation object to the positive ideal solution and the negative ideal solution is calculated:

10. The method according to claim 9, characterized in that In step S9, the comprehensive evaluation value C of each scheme is calculated: Based on the comprehensive evaluation value C of each plan, a comparative evaluation was conducted on the site suitability of the integrated construction of marine ranches and offshore wind power in each plan.

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