An evaluation method and system for offshore renewable energy development

Abstract

The application discloses an offshore renewable energy development evaluation method and system, which comprises the following steps: obtaining offshore renewable energy development data; using a fuzzy analytic hierarchy process to evaluate the offshore renewable energy development data to obtain a preliminary evaluation result; determining index weights for evaluating the offshore renewable energy development data based on the preliminary evaluation result; performing index value assignment and data standardization processing on the index weights to obtain a comprehensive evaluation result according to the processing result. The application can effectively evaluate offshore renewable energy development.

Description

Technical Field

[0001] This invention relates to the field of energy assessment technology, and in particular to an assessment method and system for the development of offshore renewable energy. Background Technology

[0002] A comparison of the current status of offshore renewable energy development and utilization at home and abroad reveals that my country's offshore renewable energy development started relatively late, has a small scale, low resource utilization, and slow development. Only offshore wind energy and marine biomass energy have a relatively small gap with international standards. The main reasons for this are as follows:

[0003] (1) Gap in technological research and development. The EU has established a marine energy experimental base in the UK, providing an experimental platform for various wave energy and ocean current energy technologies in European countries. This research and development mechanism, led by the government and involving enterprises and research institutions, greatly reduces investment budgets and accelerates the commercialization process of developed devices. In contrast, my country's marine energy research and development projects are mainly carried out by independent research units, resulting in a fragmented research effort. Even when China obtains national key projects in tidal energy, wave energy, current energy, and ocean thermal energy, the lack of industrialization and insufficient funding leads to unsatisfactory research results, seriously affecting the development progress of marine renewable energy.

[0004] (2) Gap in R&D investment. Currently, the scale of investment in commercial tidal power plants in operation abroad is relatively large. However, my country's investment in marine energy development and utilization is very small.

[0005] (1) Based on the survey and evaluation of offshore renewable energy in my country's coastal waters, and according to the development potential of offshore renewable energy, a development and utilization plan for my country's offshore renewable energy should be formulated. Currently, marine energy resource data are all from the 1980s, with only offshore wind energy having the latest resource statistics, but the scope of statistical results from different departments varies considerably. At the same time, with changes in the marine environment and the impact of engineering construction, the resource status has changed significantly.

[0006] (2) Encourage diversified operations and comprehensive utilization of marine renewable energy. For example, tidal power generation can be combined with aquaculture, wave power generation devices can be equipped with wind power devices on top, and marine renewable energy development can be combined with marine engineering (cross-sea bridges, wharves, ports and breakwaters, etc.) to carry out comprehensive utilization such as seawater desalination, aquaculture and tourism.

[0007] (3) Develop environmental guidelines for assessing the development of offshore renewable energy. Environmental issues in the development and utilization of offshore renewable energy are one of the major obstacles to its development and utilization.

[0008] (1) Research on high-efficiency energy conversion and low-cost offshore renewable energy devices. Currently, the cost of offshore renewable energy power generation devices is mostly much higher than that of conventional energy, and the energy conversion efficiency is low, which seriously restricts the large-scale and commercial development of offshore renewable energy.

[0009] (2) Research on the reliability and stability of offshore renewable energy devices, especially the typhoon resistance of wave energy, tidal energy, and thermal energy devices. Due to the extremely harsh marine environment in which offshore renewable energy devices are located, the problem of device reliability and stability must be solved in order to realize the effective utilization of offshore renewable energy.

[0010] (3) Research on corrosion-resistant materials and anti-marine biofouling technology for underwater devices for marine renewable energy.

[0011] (4) Optimization research on power plant operation, such as the large-scale development of tidal power plants, to improve the economic benefits of power plants. Summary of the Invention

[0012] The present invention aims to at least partially solve one of the technical problems in the related art.

[0013] Therefore, an evaluation method for offshore renewable energy development was designed. Improving the accuracy of the evaluation of offshore renewable energy development is beneficial to investment and construction.

[0014] To achieve the above objectives, another aspect of the present invention proposes an evaluation system for the development of offshore renewable energy.

[0015] To achieve the above objectives, this invention proposes, in one aspect, an evaluation method for offshore renewable energy development, comprising:

[0016] Obtain data on the development of offshore renewable energy;

[0017] Preliminary evaluation results were obtained by using fuzzy hierarchical analysis to evaluate the development data of offshore renewable energy.

[0018] Based on the preliminary evaluation results, the weights of the indicators used to evaluate the development data of offshore renewable energy are determined;

[0019] The weights of the indicators are assigned values ​​and the data is standardized to obtain a comprehensive evaluation result based on the processing results.

[0020] The evaluation method for offshore renewable energy development in this embodiment of the invention may also have the following additional technical features:

[0021] In one embodiment of the present invention, the method further includes:

[0022] A hierarchical structure is constructed using a hierarchical model; wherein, the hierarchical structure includes a comprehensive target layer, a criterion layer, and indicator layers;

[0023] Construct the judgment matrix:

[0024]

[0025] Among them, a ij This indicates the importance of the i-th indicator compared to the j-th indicator.

[0026] In one embodiment of the present invention, the method further includes: performing a consistency check on the judgment matrix.

[0027] Eigenvalues ​​and eigenvectors are calculated using the following formula:

[0028] A·w=λ max ·w

[0029] Where w is the eigenvector of matrix A, and λmax is its largest eigenvalue; the eigenvector is obtained by the square root method from the following formula:

[0030]

[0031] Where n represents the number of pairwise comparison criteria in the matrix;

[0032]

[0033] The consistency of a matrix is ​​determined by the negative average of its eigenvalues ​​other than the largest eigenvalue.

[0034]

[0035] In one embodiment of the present invention, the final weight ranking is as follows:

[0036]

[0037] in, The final weight of indicator i, w, is derived from K experts and decision-makers. i k It is the weight of indicator i determined by the kth expert or decision-maker, and K is the number of all experts and decision-makers.

[0038] In one embodiment of the present invention, the quantified indicators are subjected to data standardization processing. The standardization method is as follows:

[0039] The larger the better indicator:

[0040]

[0041] The larger the better indicator:

[0042]

[0043] The smaller the better indicator:

[0044]

[0045] Relatively smaller is better indicators:

[0046]

[0047] Among them, y i For the standardized data, x i x represents the original data value. max x is the maximum value in the data series. min It is the minimum value in the data series.

[0048] To achieve the above objectives, a second aspect of this application proposes an evaluation system for offshore renewable energy development, comprising:

[0049] Develop a data acquisition module to acquire development data for offshore renewable energy;

[0050] The hierarchical analysis module is used to evaluate the development data of offshore renewable energy using the fuzzy hierarchical analysis method to obtain preliminary evaluation results;

[0051] The indicator weight calculation module is used to determine the indicator weights for evaluating the development data of offshore renewable energy based on the preliminary evaluation results.

[0052] The comprehensive evaluation module is used to assign values ​​to the indicator weights and perform data standardization processing to obtain a comprehensive evaluation result based on the processing results.

[0053] The evaluation method and system for offshore renewable energy development in this invention, through accurate evaluation, can achieve higher energy utilization efficiency, lower costs, better system reliability and safety, while promoting technological innovation and standardization, enhancing environmental and social benefits, and gaining policy and market support.

[0054] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0055] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0056] Figure 1 This is a flowchart of an evaluation method for offshore renewable energy development according to an embodiment of the present invention.

[0057] Figure 2 This is a judgment matrix scale and meaning diagram according to an embodiment of the present invention.

[0058] Figure 3It is the index RI value according to an embodiment of the present invention.

[0059] Figure 4 This is a schematic diagram of an evaluation system for offshore renewable energy development according to an embodiment of the present invention. Detailed Implementation

[0060] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0061] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0062] The following describes an evaluation method for offshore renewable energy development based on an embodiment of the present invention, with reference to the accompanying drawings.

[0063] Figure 1 This is a flowchart of an evaluation method for offshore renewable energy development according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes:

[0064] S1, to acquire data on the development of offshore renewable energy;

[0065] S2, using fuzzy hierarchical analysis to evaluate the development data of offshore renewable energy and obtain preliminary evaluation results;

[0066] S3, Based on the preliminary evaluation results, determine the indicator weights for evaluating the development data of offshore renewable energy;

[0067] S4. Assign values ​​to the indicator weights and standardize the data to obtain a comprehensive evaluation result based on the processing results.

[0068] This invention first uses fuzzy hierarchical analysis to evaluate the development of offshore renewable energy to determine the weights of indicators, and then performs indicator assignment and data standardization to obtain the comprehensive evaluation results.

[0069] (1) Constructing the hierarchical analysis structure

[0070] The hierarchical structure model is the foundation of AHP analysis. It decomposes complex problems into multiple indicators or criteria and forms a hierarchical structure based on their relationships and hierarchical relationships, namely the comprehensive goal layer, the criterion layer, and the indicator layer.

[0071] (2) Construct the judgment matrix

[0072] To quantify decision-making, it is necessary to compare the importance of indicators at the same level. The assigned values ​​are obtained by the analyst through consultation with decision-makers and relevant experts. This invention employs a 1-9 scale for quantification. Figure 2 As shown.

[0073] Generally, the form of a judgment matrix is ​​as follows;

[0074]

[0075] Among them, a ij This indicates the importance of the i-th indicator compared to the j-th indicator.

[0076] (3) Consistency test of the judgment matrix

[0077] In solving practical problems, the constructed judgment matrix may not be consistent and a consistency check is required.

[0078] Eigenvalues ​​and eigenvectors are calculated using the following formula:

[0079] A·w=λ max ·w

[0080] Where w is the eigenvector of matrix A, and λmax is its largest eigenvalue; the eigenvector is obtained by the square root method from the following formula:

[0081]

[0082] Where n represents the number of pairwise comparison criteria in the matrix;

[0083]

[0084] The consistency of a matrix is ​​determined by the negative average of its eigenvalues ​​other than the largest eigenvalue.

[0085]

[0086] A smaller CI value indicates better consistency. Conversely, a larger CI value indicates a greater deviation from perfect consistency. For different judgment matrices, the RI value varies as follows: Figure 3 As shown.

[0087] when When the judgment matrix is ​​consistent, it is considered to be consistent.

[0088] (4) Final weight ranking:

[0089]

[0090] in, The final weight of indicator i, w, is derived from K experts and decision-makers. i k It is the weight of indicator i determined by the kth expert or decision-maker, and K is the number of all experts and decision-makers.

[0091] (5) Indicator assignment and data standardization

[0092] For quantitative indicators, data can be obtained from literature, research reports, or through direct calculation. For qualitative indicators, a scoring system of 1 to 9 points is used, with a maximum of 9 and a minimum of 1 for relative conditions. Next, we need to standardize the data for these quantitative indicators. Common indicator types are categorized into four types: absolutely larger is better, relatively larger is better, absolutely smaller is better, and relatively smaller is better. The standardization methods are as follows:

[0093] The larger the better indicator:

[0094]

[0095] The larger the better indicator:

[0096]

[0097] The smaller the better indicator:

[0098]

[0099] Relatively smaller is better indicators:

[0100]

[0101] Among them, y i For the standardized data, x i x represents the original data value. max x is the maximum value in the data series. min It is the minimum value in the data series.

[0102] (6) Overall Evaluation Results

[0103] Based on the assignment of values ​​and data standardization of qualitative and quantitative indicators, a linear weighting method is used for indicators belonging to the same criterion layer to obtain comprehensive evaluation values ​​for each criterion layer. For example, in Dalian City, the technical, economic, resource, environmental, and safety evaluation values ​​for renewable energy development and utilization are calculated. Then, a linear weighting method is used to couple the evaluation values ​​from the five criterion layers (technical, economic, resource, environmental, and safety) to obtain the final evaluation results for different types of energy, which are then ranked. A higher comprehensive score indicates that the energy source is easier to utilize under the evaluation benchmark than other alternatives and should be given priority for development.

[0104] With economic development and energy consumption, energy development and utilization have also developed rapidly. When conducting a comprehensive evaluation, we should not only consider the current situation, but also look to the future and consider the future trend of the indicators.

[0105] According to the evaluation method for offshore renewable energy development of embodiments of the present invention, the following advantages are achieved: Improved energy utilization efficiency and optimized design and layout: Through precise assessment of wind, wave, and tidal resources, the design and layout of offshore wind farms, wave energy converters, and tidal power stations can be optimized. For example, high-precision meteorological models and ocean dynamics models are used to determine the optimal equipment location to maximize energy capture. Intelligent operation and maintenance: Utilizing big data analytics and artificial intelligence technologies, the operating status of equipment is monitored in real time, maintenance needs are predicted, downtime is reduced, and the availability and efficiency of the overall system are improved. Reduced construction and operating costs and precise site selection: Through detailed geological exploration and environmental assessment, the most suitable sea area for construction is selected, avoiding potential geological risks and ecological impacts, thereby reducing construction difficulty and costs. Technological innovation: Promoting the research and development of new materials and technologies, such as lighter, corrosion-resistant materials and efficient energy conversion devices, to reduce costs and extend equipment life. Supply chain optimization: Through precise management of the supply chain, the quality and supply stability of equipment and materials are ensured, reducing cost increases due to delays or quality problems. Enhanced system reliability and safety: Structural safety: Through precise engineering calculations and simulations, the structural safety of offshore facilities under extreme weather conditions is ensured, reducing failure rates and maintenance frequency. Environmental Protection: Accurately assess the project's impact on the marine ecosystem and implement corresponding protective measures, such as establishing protected areas and limiting noise pollution, to ensure the project's sustainability. Risk Warning: Establish a comprehensive risk management system, combining real-time monitoring data to promptly identify and address potential safety hazards, such as equipment failures and changes in sea conditions. Promoting Technological Innovation and Standardization: Precise evaluation helps identify the shortcomings of existing technologies, promoting the development of new technological solutions, such as more efficient energy conversion technologies and more reliable submarine cable technologies. Standardization: Through extensive data analysis and experience summarization, formulate industry standards and technical specifications to promote the healthy development of the entire industry and enhance international competitiveness. Enhancing Environmental and Social Benefits: Reducing Environmental Impact: Through precise assessment and planning, minimize negative impacts on marine life and the ecological environment, achieving green development. Social Benefits: Precise evaluation helps governments and enterprises better understand the project's social impact, such as employment opportunities and community development, thereby developing more targeted social responsibility plans. Policy Support and Market Access: Providing scientific evidence to help governments formulate more reasonable and effective policies to support the development of offshore renewable energy. Market Access: Through precise evaluation, demonstrate the project's feasibility and economic viability, providing strong support for project financing and market access.

[0106] like Figure 4As shown, the present invention also proposes an evaluation system 10 for offshore renewable energy development, comprising:

[0107] The development data acquisition module 100 is used to acquire development data of offshore renewable energy.

[0108] The hierarchical analysis module 200 is used to evaluate the development data of offshore renewable energy using the fuzzy hierarchical analysis method to obtain preliminary evaluation results;

[0109] The indicator weight calculation module 300 is used to determine the indicator weights for evaluating the development data of offshore renewable energy based on the preliminary evaluation results.

[0110] The comprehensive evaluation module 400 is used to assign values ​​to the indicator weights and perform data standardization processing to obtain a comprehensive evaluation result based on the processing results.

[0111] Furthermore, it is also used for:

[0112] A hierarchical structure is constructed using a hierarchical model; wherein, the hierarchical structure includes a comprehensive target layer, a criterion layer, and indicator layers;

[0113] Construct the judgment matrix:

[0114]

[0115] Among them, a ij This indicates the importance of the i-th indicator compared to the j-th indicator.

[0116] Furthermore, it is also used for: consistency checks on the judgment matrix:

[0117] Eigenvalues ​​and eigenvectors are calculated using the following formula:

[0118] A·w=λ max ·w

[0119] Where w is the eigenvector of matrix A, and λmax is its largest eigenvalue; the eigenvector is obtained by the square root method from the following formula:

[0120]

[0121] Where n represents the number of pairwise comparison criteria in the matrix;

[0122]

[0123] The consistency of a matrix is ​​determined by the negative average of its eigenvalues ​​other than the largest eigenvalue.

[0124]

[0125] Furthermore, it is also used for: sorting the final weights:

[0126]

[0127] in, The final weight of indicator i, w, is derived from K experts and decision-makers. i k It is the weight of indicator i determined by the kth expert or decision-maker, and K is the number of all experts and decision-makers.

[0128] Furthermore, the quantified indicators undergo data standardization processing:

[0129] The larger the better indicator:

[0130]

[0131] The larger the better indicator:

[0132]

[0133] The smaller the better indicator:

[0134]

[0135] Relatively smaller is better indicators:

[0136]

[0137] Among them, y i For the standardized data, x i x represents the original data value. max x is the maximum value in the data series. min It is the minimum value in the data series.

[0138] According to embodiments of the present invention, the evaluation system for offshore renewable energy development improves energy utilization efficiency and optimizes design and layout: Through precise assessment of wind, wave, and tidal resources, the design and layout of offshore wind farms, wave energy converters, and tidal power stations can be optimized. For example, high-precision meteorological models and ocean dynamics models are used to determine the optimal equipment location to maximize energy capture. Intelligent operation and maintenance: Utilizing big data analytics and artificial intelligence technologies, the system monitors equipment operating status in real time, predicts maintenance needs, reduces downtime, and improves the overall system availability and efficiency. Reduced construction and operating costs: Precise site selection: Through detailed geological exploration and environmental assessment, the most suitable sea area for construction is selected, avoiding potential geological risks and ecological impacts, thereby reducing construction difficulty and costs. Technological innovation: The system promotes the research and development of new materials and technologies, such as lighter, corrosion-resistant materials and more efficient energy conversion devices, to reduce costs and extend equipment life. Supply chain optimization: Through precise supply chain management, the quality and supply stability of equipment and materials are ensured, reducing cost increases due to delays or quality issues. Enhanced system reliability and safety: Structural safety: Through precise engineering calculations and simulations, the structural safety of offshore facilities under extreme weather conditions is ensured, reducing failure rates and maintenance frequency. Environmental Protection: Accurately assess the project's impact on the marine ecosystem and implement corresponding protective measures, such as establishing protected areas and limiting noise pollution, to ensure the project's sustainability. Risk Warning: Establish a comprehensive risk management system, combining real-time monitoring data to promptly identify and address potential safety hazards, such as equipment failures and changes in sea conditions. Promoting Technological Innovation and Standardization: Precise evaluation helps identify the shortcomings of existing technologies, promoting the development of new technological solutions, such as more efficient energy conversion technologies and more reliable submarine cable technologies. Standardization: Through extensive data analysis and experience summarization, formulate industry standards and technical specifications to promote the healthy development of the entire industry and enhance international competitiveness. Enhancing Environmental and Social Benefits: Reducing Environmental Impact: Through precise assessment and planning, minimize negative impacts on marine life and the ecological environment, achieving green development. Social Benefits: Precise evaluation helps governments and enterprises better understand the project's social impact, such as employment opportunities and community development, thereby developing more targeted social responsibility plans. Policy Support and Market Access: Providing scientific evidence to help governments formulate more reasonable and effective policies to support the development of offshore renewable energy. Market Access: Through precise evaluation, demonstrate the project's feasibility and economic viability, providing strong support for project financing and market access.

[0139] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0140] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

Claims

1. An evaluation method for offshore renewable energy development, characterized in that, include: Obtain data on the development of offshore renewable energy; Preliminary evaluation results were obtained by using fuzzy hierarchical analysis to evaluate the development data of offshore renewable energy. Based on the preliminary evaluation results, the weights of the indicators used to evaluate the development data of offshore renewable energy are determined; The weights of the indicators are assigned values ​​and the data is standardized to obtain a comprehensive evaluation result based on the processing results.

2. The method according to claim 1, characterized in that, The method further includes: A hierarchical structure is constructed using a hierarchical model; wherein, the hierarchical structure includes a comprehensive target layer, a criterion layer, and indicator layers; Construct the judgment matrix: Among them, a ij This indicates the importance of the i-th indicator compared to the j-th indicator.

3. The method according to claim 2, characterized in that, The method further includes: a consistency check of the judgment matrix. Eigenvalues ​​and eigenvectors are calculated using the following formula: A·w=λ max ·w Where w is the eigenvector of matrix A, and λmax is its largest eigenvalue; the eigenvector is obtained by the square root method from the following formula: Where n represents the number of pairwise comparison criteria in the matrix; The consistency of a matrix is ​​determined by the negative average of its eigenvalues ​​other than the largest eigenvalue.

4. The method according to claim 3, characterized in that, Final weight ranking: in, It is the final weight of indicator i derived by K experts and decision-makers. It is the weight of indicator i determined by the kth expert or decision-maker, and K is the number of all experts and decision-makers.

5. The method according to claim 4, characterized in that, The quantitative indicators undergo data standardization processing. The standardization method is as follows: The larger the better indicator: The larger the better indicator: The smaller the better indicator: Relatively smaller is better indicators: Among them, y i For the standardized data, x i x represents the original data value. max x is the maximum value in the data series. min It is the minimum value in the data series.

6. An evaluation system for offshore renewable energy development, characterized in that, include: Develop a data acquisition module to acquire development data for offshore renewable energy; The hierarchical analysis module is used to evaluate the development data of offshore renewable energy using the fuzzy hierarchical analysis method to obtain preliminary evaluation results; The indicator weight calculation module is used to determine the indicator weights for evaluating the development data of offshore renewable energy based on the preliminary evaluation results. The comprehensive evaluation module is used to assign values ​​to the indicator weights and perform data standardization processing to obtain a comprehensive evaluation result based on the processing results.

7. The system according to claim 6, characterized in that, Also used for: A hierarchical structure is constructed using a hierarchical model; wherein, the hierarchical structure includes a comprehensive target layer, a criterion layer, and indicator layers; Construct the judgment matrix: Among them, a ij This indicates the importance of the i-th indicator compared to the j-th indicator.

8. The system according to claim 7, characterized in that, It is also used for consistency checks on the judgment matrix: Eigenvalues ​​and eigenvectors are calculated using the following formula: A·w=λ max ·w Where w is the eigenvector of matrix A, and λmax is its largest eigenvalue; The eigenvectors are obtained using the square root method from the following formula: Where n represents the number of pairwise comparison criteria in the matrix; The consistency of a matrix is ​​determined by the negative average of its eigenvalues ​​other than the largest eigenvalue.

9. The system according to claim 8, characterized in that, Final weight ranking: in, It is the final weight of indicator i derived by K experts and decision-makers. It is the weight of indicator i determined by the kth expert or decision-maker, and K is the number of all experts and decision-makers.

10. The system according to claim 9, characterized in that, Standardize the data for quantified indicators: The larger the better indicator: The larger the better indicator: The smaller the better indicator: Relatively smaller is better indicators: Among them, y i For the standardized data, x i x represents the original data value. max x is the maximum value in the data series. min It is the minimum value in the data series.

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