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针对目前波浪能开发适宜性分析方法存在的问题及工作量大、成本高的特点，基于地理信息系统(Geographic information system, GIS)、改进的多准则决策方法(Multi-criteria decision making, MCDM)和人工神经网络(Artificial neural network, ANN)提出海南省波浪能开发智能化适宜性分析模型。对于该模型：首先，使用模糊层次分析(Fuzzy analytic hierarchy process, FAHP)法计算评价指标权重，降低专家主观偏差，更好地描述信息的不确定性；其次，提出灰色关联分析-折衷优化(Grey relation analysis-vlse kriterijumska optimizacijaⅠkompromisno resenje, GRA-VIKOR)法计算开发适宜性指数，解决评价过程中部分信息丢失、评价结果不准确的问题；最后依托反向传播(Back propagation, BP)神经网络进行模型训练并进行验证，实现海南省波浪能开发适宜性分析的智能化，不仅提高工作效率，而且降低计算成本。通过模型得到海南省波浪能可开发区域和开发适宜性等级，为海南省波浪能选址决策奠定基础，同时可填补海南省波浪能开发适宜性分析在智能化领域的空白。
Abstract：In view of the problems existing in the current wave energy development suitability analysis method and the characteristics of large workload and high cost, this paper proposes an intelligent suitability analysis model for wave energy development in Hainan Province based on geographic information system(GIS), improved multi-criteria decision making(MCDM) and artificial neural network(ANN). In this model, fuzzy analytic hierarchy process(FAHP) is used to calculate the weight of evaluation criteria, which can reduce the subjective bias of experts and better describe the uncertainty of information. Grey relation analysis-vlse kriterijumska optimizacija Ⅰ kompromisno resenje(GRA-VIKOR) is proposed to calculate the suitability index, which solves the problems of partial information loss and inaccurate evaluation results in the evaluation process. The model is trained and verified based on back propagation(BP) neural network to realize the intelligence. The feasible areas and suitability levels of wave energy in Hainan province are obtained by the model, which lays a foundation for the site selection decision making of wave energy in Hainan Province and fills the gap in the field of intelligent wave energy development suitability analysis.
[1] 刘志远.深耕“蓝色沃土”,海洋能助力实现“碳中和”——访浙江大学教授李伟[J].科技导报，2021,39(6):18-21.Liu Z Y.Deeply cultivating fertile blue soil,ocean energy helps achieve carbon neutrality[J].Science and Technology Review,2021,39(6):18-21.
[2] 国家能源局.“十四五”现代能源体系规划[EB/OL].(2022-03-23)https://www.gov.cn/zhengce/zhengceku/2022-03/23/5680759/files/ccc7dffca8f24880a80af12755558f4a.pdf.National Energy Administration.The 14th Five-Year Plan for Modern Energy System[EB/OL].(2022-03-23)https://www.gov.cn/zhengce/zhengceku/2022-03/23/5680759/files/ccc7dffca8f 24880a80af12755558f4a.pdf.
[3] Wen Y,Kamranzad B,Lin P.Joint exploitation potential of offshore wind and wave energy along the south and southeast coasts of China[J].Energy,2022,249:123710.
[4] 王项南，麻常雷.“双碳”目标下海洋可再生能源资源开发利用[J].华电技术，2021,43(11):91-96.Wang X N,Ma C L.Utilization of marine renewable energy resources under the goal of carbon peaking and carbon neutrality[J].Huadian Technology,2021,43(11):91-96.
[5] 刘伟民，刘蕾，陈凤云，等.中国海洋可再生能源技术进展[J].科技导报，2020,38(14):27-39.Liu W M,Liu L,Chen F Y,et al.Technical progress of marine renewable energy in China[J].Science and Technology Review,2020,38(14):27-39.
[6] 海南省自然资源和规划厅.海南省海洋经济发展 “十四五” 规划(2021—2025年) [EB/OL].(2021-06-08).http://lr.hainan.gov.cn/xxgk_317/0200/0202/202106/t20210608_2991346.html.Department of Natural Resources and Planning of Hainan Province.Hainan Province′s 14th Five-Year Plan for Marine Economic Development (2021—2025)[EB/OL].(2021-06-08).http://lr.hainan.gov.cn/xxgk_317/0200/0202/202106/t20210608_2991346.html.
[7] 邵萌，史宏达，赵阳，等.基于改进层次分析法的海洋能多能互补选址决策模型[J].太阳能学报，2016,37(9):2443-2450.Shao M,Shi H D,Zhao Y,et al.Location decision model of hybrid marine energy based on improved AHP method[J].Acta Energiae Solaris Sinica,2016,37(9):2443-2450.
[8] Shao M,Han Z X,Sun J W,et al.A review of multi-criteria decision making applications for renewable energy site selection[J].Renewable Energy,2020,157:377-403.
[9] Mahdy M,Bahaj A S.Multi criteria decision analysis for offshore wind energy potential in Egypt[J].Renewable Energy,2018,118:278-289.
[10] Vinhoza A,Schaeffer R.Brazil′s offshore wind energy potential assessment based on a spatial multi-criteria decision analysis[J].Renewable and Sustainable Energy Reviews,2021,146:111185.
[11] Bahaj A S,Mahdy M,Alghamdi A S,et al.New approach to determine the importance index for developing offshore wind energy potential sites:Supported by UK and Arabian Peninsula case studies[J].Renewable Energy,2020,152:441-457.
[12] Akbari N,Irawan C A,Jones D F,et al.A multi-criteria port suitability assessment for developments in the offshore wind industry[J].Renewable Energy,2017,102:118-133.
[13] Ghosh S,Chakraborty T,Saha S,et al.Development of the location suitability index for wave energy production by ANN and MCDM techniques[J].Renewable and Sustainable Energy Reviews,2016,59:1017-1028.
[14] Shao M,Han Z X,Sun J W,et al.A GIS-MCDM combination for the site assessment of wave energy power station in Qingdao,eastern China[C]// The 30th International Ocean and Polar Engineering Conference.Shanghai:International Society of Offshore & Polar Engineers,2020.
[15] 邵萌，赵远续，孙金伟，等.基于GIS和多准则决策的山东省潮流能区划研究[J].中国海洋大学学报(自然科学版),2021,51(12):107-114.Shao M,Zhao Y X,Sun J W,et al.Methodology of tidal current energy zoning for Shandong province based on GIS and MCDM[J].Periodical of Ocean University of China,2021,51(12):107-114.
[16] Gil-García I C,Ramos-Escudero A,García-Cascales M S,et al.Fuzzy GIS-based MCDM solution for the optimal offshore wind site selection:The gulf of maine case[J].Renewable Energy,2022,183:130-147.
[17] Konstantinos I,Georgios T,Garyfalos A.A decision support system methodology for selecting wind farm installation locations using AHP and TOPSIS:Case study in eastern Macedonia and Thrace region,Greece[J].Energy Policy,2019,132:232-246.
[18] Ayodele T R,Ogunjuyigbe A S O,Odigie O,et al.A multi-criteria GIS based model for wind farm site selection using interval type-2 fuzzy analytichierarchy process:The case study of Nigeria[J].Applied Energy,2018,228:1853-1869.
[19] Aydogan E K.Performance measurement model for Turkish Aviation firms using the rough-AHP and TOPSIS methods under fuzzy environment[J].Expert Systems with Applications,2011,38(4):3992-3998.
[20] Taoufik M,Fekri A.GIS-based multi-criteria analysis of offshore wind farm development in Morocco[J].Energy Conversion and Management:Ⅹ,2021,11:100103.
[21] Tavana M,Santos Arteaga F J,Mohammadi S,et al.A fuzzy multi-criteria spatial decision support system for solar farm location planning[J].Energy Strategy Reviews,2017,18:93-105.
[22] Abdul D,Wenqi J,Tanveer A.Prioritization of renewable energy source for electricity generation through AHP-VIKOR integrated methodology[J].Renewable Energy,2022,184:1018-1032.
[23] Rezaei M,Alharbi S A,Razmjoo A,et al.Accurate location planning for a wind-powered hydrogen refueling station:Fuzzy VIKOR method[J].International Journal of Hydrogen Energy,2021,46(67):33360-33374.
[24] San Cristóbal J R.Multi-criteria decision-making in the selection of a renewable energy project in Spain:The VIKOR method[J].Renewable Energy,2011,36(2):498-502.
[25] 董文心，王英，张悦，等.基于DEMATEL-相关性分析和VIKOR-灰色关联分析的供应链绩效评价模型研究[J].科技管理研究，2018,38(9):191-197.Dong W X,Wang Y,Zhang Y,et al.Research on the model of supply chain performance evaluation based on DEMATEL-correlation analysis and VIKOR-gray relational analysis[J].Science and Technology Management Research,2018,38(9):191-197.
[26] Kalra R,Deo M C.Derivation of coastal wind and wave parameters from offshore measurements of TOPEX satellite using ANN[J].Coastal Engineering,2007,54(3):187-196.
[27] Wang W,Tang R,Li C,et al.A BP neural network model optimized by mind evolutionary algorithm for predicting the ocean wave heights[J].Ocean Engineering,2018,162:98-107.
[28] Sánchez-Lozano J M,Teruel-Solano J,Soto-Elvira P L,et al.Geographical information systems (GIS) and Multi-criteria decision making (MCDM) methods for the evaluation of solar farms locations:Case study in south-eastern Spain[J].Renewable and Sustainable Energy Reviews,2013,24:544-556.
[29] Zadeh L A.Fuzzy sets[J].Information and Control,1965,8:8338-8353.
[30] Opricovic S,Tzeng G.Extended VIKOR method in comparisonwith outranking methods[J].European Journal of Operational Research,2007,178(2):514-529.
[31] Zeleny M.Multiple Criteria Decision Making[M].New York:McGraw-Hill,1982.
[32] 邓聚龙.灰色系统理论和方法[M].武汉：华中工学院出版社，1987.Deng J L.Grey System Theory and Methods[M].Wuhan:Huazhong Institute of Technology Press,1987.
[33] 海南省生态环境厅.海南省生态保护红线管理规定[EB/OL].(2016-08-08).http://hnsthb.hainan.gov.cn/xxgk/0200/0202/hjywgl/stbh/201901/t20190106_2126022_mo.html.Department of Ecology and Environment of Hainan Province.Hainan ecological protection red line management regulations[EB/OL].(2016-08-08).http://hnsthb.hainan.gov.cn/xxgk/0200/0202/hjywgl/stbh/201901/t20190106_2126022_mo.html.
[34] Liang B,Gao H,Shao Z.Characteristics of global waves based on the third-generation wave model SWAN[J].Marine Structures,2019,64:35-53.
[35] 邵萌，张淑蕾，孙金伟，等.基于多准则决策方法的海岛风浪互补电站选址决策研究[J].中国海洋大学学报(自然科学版),2022,52(4):120-129.Shao M,Zhang S L,Sun J W,et al.Research on site selection methodology of wind-wave hybrid power plant for islands based on MCDM[J].Periodical of Ocean University of China,2022,52(4):120-129.
[36] Zhou X,Huang Z,Wang H,et al.Site selection for hybrid offshore wind and wave power plants using a four-stage framework:A case study in Hainan,China[J].Ocean & Coastal Management,2022,218:106035.
[37] 海南省统计局.海南省第七次人口普查公告[EB/OL].(2021-05-13) http://stats.hainan.gov.cn/tjj/ztzl/rkpc/pcyw/202105/t2 0210512_2977751.html.Hainan Provincial Bureau of Statistics.Announcement of the Seventh Population Census of Hainan Province[EB/OL].(2021-05-13).http://stats.hainan.gov.cn/tjj/ztzl/rkpc/pcyw/202105/t202 10512_2977751.html.
[38] 周政.BP神经网络的发展现状综述[J].山西电子技术，2008(2):90-92.Zhou Z.Survey of current progress in BP neural network[J].Shanxi Electronic Technology,2008(2):90-92.
[39] Hecht-Nielsen R.Kolmogorov’s mapping neural net- works existence theorem[C]//Proceedings of the Institute of Electrical and Electronics Engineers First International Conference on Neural Networks.New York:Institute of Electrical and Electronics Engineers,1987:11-13.
[40] Guo Z H,Wu J,Lu H,et al.A case study on a hybrid wind speed forecasting method using BP neural network[J].Renewable Energy,2011,24:1048-1056.
基本信息:
DOI：10.16441/j.cnki.hdxb.20220343
中图分类号:P743.2
引用信息:
[1]邵萌,伊传秀,陈玉静,等.海南省波浪能开发智能化适宜性分析模型研究[J].中国海洋大学学报(自然科学版),2024,54(06):165-178.DOI:10.16441/j.cnki.hdxb.20220343.
基金信息:
国家重点研究发展计划项目(2022YFC3104201); 国家自然科学基金项目(51609224); 山东省自然科学基金项目(ZR2023ME028,ZR2020QE297,ZR2020ME259); 中国工程院战略研究与咨询项目(2022-DFZD-36)资助~~
2022-07-14
2022
2022-11-27
2022-12-06
2022
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2024-05-30
2024-05-30