基于模糊证据理论的风电场海缆路由方案选择研究
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摘要
为合理规划风电场海上路由,保障船舶航行安全和节约运营成本,研究了基于模糊证据理论的风电场海缆路由方案选择方法。识别了风电场海缆路由规划的影响因素,建立了海缆路由的3层决策框架。利用模糊隶属度函数对影响因素进行模糊化,并引入置信度建立了置信推理规则库,建立了影响因素与决策变量的模糊转换方法,并引入证据理论对转换后的影响因素进行合成,从而实现海缆路由的最优选择。以浙能风电场海缆路由选择为例,确定了浙能风电场海缆路由的规划方案。结果表明,该模型能够充分考虑通航安全对风电场海缆路由的影响,且能够解决对通航安全因素模糊推理过程中不能精确描述输出变量的问题,因此,能够为风电场海缆路由方案选择提供定量和可靠的评价工具。
In order to plan pipeline routing of offshore wind farms and to ensure maritime safety as well as reduce operational costs, a method based on fuzzy evidential reasoning for pipeline routing of offshore wind farms is proposed. Influencing factors are identified from previous studies, based on which a three-layer decision-making framework is established for pipeline routing. Then the influencing factors are fuzzified by using membership functions, and belief degree is introduced to describe output variables. Fuzzy transformation technique is applied to transform the influencing factors into decision variables, and evidential reasoning is utilized to integrate all influencing factors. Taking site selection of offshore wind farms in Shanghai as a case study, a site selection scheme in far-reaching sea areas of Shanghai is established. This model can comprehensively consider the influences of maritime safety when selecting pipeline routing, and address problems of cannot accurately describe the output variables in IF-THEN rules scheme. Consequently, it provides a quantitative and useful tool for site selection of offshore wind farms in far-reaching sea areas.
In order to plan pipeline routing of offshore wind farms and to ensure maritime safety as well as reduce operational costs, a method based on fuzzy evidential reasoning for pipeline routing of offshore wind farms is proposed. Influencing factors are identified from previous studies, based on which a three-layer decision-making framework is established for pipeline routing. Then the influencing factors are fuzzified by using membership functions, and belief degree is introduced to describe output variables. Fuzzy transformation technique is applied to transform the influencing factors into decision variables, and evidential reasoning is utilized to integrate all influencing factors. Taking site selection of offshore wind farms in Shanghai as a case study, a site selection scheme in far-reaching sea areas of Shanghai is established. This model can comprehensively consider the influences of maritime safety when selecting pipeline routing, and address problems of cannot accurately describe the output variables in IF-THEN rules scheme. Consequently, it provides a quantitative and useful tool for site selection of offshore wind farms in far-reaching sea areas.
引文
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[13] 唐征歧,江建平,李子林,等.深远海域海上风电场定量选址方法研究[J].交通信息与安全,2018(2):106-111. TANG Zhengqi, JIANG Jianping, LI Zilin, et al.A quantitative method for site selection of offshore wind farms in far-reaching sea areas[J]. Journal of Transport Information and Safety, 2018(2):106-111.(in Chinese)
[14] 王燕青,刘媛媛.X光机操作员视觉搜索作业疲劳模糊综合评价[J].交通信息与安全,2016,34(4):78-84. WANG Yanqing ,LIU Yuanyuan. A Fuzzy Synthetic Evaluation Method to Visual Fatigue for X-Ray Machine Operators[J]. Journal of Transport Information and Safety, 2016,34(4):78-84.(in Chinese)
[15] 黄影,吴兵,郭国平.多重模糊条件下的水上服务区类型决策[J].船海工程,2017,46(1):167-172. HUANG Ying,WU Bing, GUO Guoping.Research for type selection of waterway service area under multiple-fuzziness [J]. Ship & Ocean Engineering, 2017,46(1):167-172. (in Chinese)
[16] 吴兵,严新平,汪洋,等.不确定性信息下的内河失控船应急决策方法[J].哈尔滨工程大学学报,2016,37(7):908-914. WU Bing, YAN Xinping, WANG Yang, et al. Emergency decision-making method for handling an out-of-control ship in inland water in case of uncertain information. Journal of HarbinEngineering University, 2016,37(7):908-914. (in Chinese)
[17] YANG J B, LIU J, WANG J, et al. Belief rule-base inference methodology using the evidential reasoning Approach-RIMER[J]. IEEE Transactions on Systems Man & Cybernetics Part A Systems & Humans, 2006,36(2):266-285.
[18] YANG Z L, WANG J, BONSALL S, et al. Use of Fuzzy Evidential Reasoning in Maritime Security Assessment[J]. Risk Analysis, 2010,29(1):95-120.
[2] CASTRO-SANTOS L, DIAZ-CASAS V. Economic influence of location in floating offshore wind farms[J]. Ocean Engineering, 2015(107):13-22.
[3] BARLOW E, ?ZTüRK D T, REVIE M, et al. Exploring the impact of innovative developments to the installation process for an offshore wind farm[J]. Ocean Engineering, 2015(109):623-634.
[4] PATERSON J, D′AMICO F, THIES P R, et al. Offshore wind installation vessels-A comparative assessment for UK offshore rounds 1 and 2[J]. Ocean Engineering, 2017(148):637-649.
[5] IRAWAN C A, OUELHADJ D, JONES D, et al. Optimisation of maintenance routing and scheduling for offshore wind farms[J]. European Journal of Operational Research, 2017,256(1):76-89.
[6] RINALDI G, THIES P R, WALKER R, et al. A decision support model to optimise the operation and maintenance strategies of an offshore renewable energy farm[J]. Ocean Engineering, 2017(145):250-262.
[7] CHAOUACHI A, COVRIG C F, ARDELEAN M. Multi-criteria selection of offshore wind farms: Case study for the Baltic States[J]. Energy Policy, 2017(103):179-192.
[8] FETANAT A, KHORASANINEJAD E. A novel hybrid MCDM approach for offshore wind farm site selection: A case study of Iran[J]. Ocean & Coastal Management, 2015(109):17-28.
[9] WU Y, ZHANG J, YUAN J, et al. Study of decision framework of offshore wind power station site selection based on ELECTRE-III under intuitionistic fuzzy environment: A case of China[J]. Energy Conversion & Management, 2016(113):66-81.
[10] BALOGUN A L, MATORI A N, HAMID-MOSAKU A I. A fuzzy multi-criteria decision support system for evaluating subsea oil pipeline routing criteria in East Malaysia[J]. Environmental Earth Sciences, 2015,74(6):1-10.
[11] DEY P K. Integrated project evaluation and selection using multiple-attribute decision-making technique[J]. International Journal of Production Economics, 2006,103(1):90-103.
[12] Wu B, Yip T L, Xie L, et al. A fuzzy-MADM based approach for site selection of offshore wind farm in busy waterways in China[J]. Ocean Engineering, 2018(168):121-132.
[13] 唐征歧,江建平,李子林,等.深远海域海上风电场定量选址方法研究[J].交通信息与安全,2018(2):106-111. TANG Zhengqi, JIANG Jianping, LI Zilin, et al.A quantitative method for site selection of offshore wind farms in far-reaching sea areas[J]. Journal of Transport Information and Safety, 2018(2):106-111.(in Chinese)
[14] 王燕青,刘媛媛.X光机操作员视觉搜索作业疲劳模糊综合评价[J].交通信息与安全,2016,34(4):78-84. WANG Yanqing ,LIU Yuanyuan. A Fuzzy Synthetic Evaluation Method to Visual Fatigue for X-Ray Machine Operators[J]. Journal of Transport Information and Safety, 2016,34(4):78-84.(in Chinese)
[15] 黄影,吴兵,郭国平.多重模糊条件下的水上服务区类型决策[J].船海工程,2017,46(1):167-172. HUANG Ying,WU Bing, GUO Guoping.Research for type selection of waterway service area under multiple-fuzziness [J]. Ship & Ocean Engineering, 2017,46(1):167-172. (in Chinese)
[16] 吴兵,严新平,汪洋,等.不确定性信息下的内河失控船应急决策方法[J].哈尔滨工程大学学报,2016,37(7):908-914. WU Bing, YAN Xinping, WANG Yang, et al. Emergency decision-making method for handling an out-of-control ship in inland water in case of uncertain information. Journal of HarbinEngineering University, 2016,37(7):908-914. (in Chinese)
[17] YANG J B, LIU J, WANG J, et al. Belief rule-base inference methodology using the evidential reasoning Approach-RIMER[J]. IEEE Transactions on Systems Man & Cybernetics Part A Systems & Humans, 2006,36(2):266-285.
[18] YANG Z L, WANG J, BONSALL S, et al. Use of Fuzzy Evidential Reasoning in Maritime Security Assessment[J]. Risk Analysis, 2010,29(1):95-120.