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摘要:
Wind power is a kind of clean energy promising significant social and environmental benefits, and in The Peoples Republic of China, the government supports and encourages the development of wind power as one element in a shift to renewable energy. In recent years however, maritime safety issues have arisen during offshore wind power construction and attendant production processes associated with the rapid promotion and development of offshore wind farms. Therefore, it is necessary to carry out risk assessment for phases in the life cycle of offshore wind farms. This paper reports on a risk assessment model based on a Dynamic Bayesian network that performs offshore wind farms maritime risk assessment. The advantage of this approach is the way in which a Bayesian model expresses uncertainty. Furthermore, such models permit simulations and reenactment of accidents in a virtual environment. There were several goals in this research. Offshore wind power project risk identification and evaluation theories and methods were explored to identify the sources of risk during different phases of the offshore wind farm life cycle. Based on this foundation, a dynamic Bayesian network model with Genie was established, and evaluated, in terms of its effectiveness for analysis of risk during different phases of the offshore wind farm life cycle. Research results show that a dynamic Bayesian network method can perform risk assessments effectively and flexibly, responding to the actual context of offshore wind power construction. Historical data and almost real-time information are combined to analyze the risk of the construction of offshore wind power. Our results inform a discussion of security and risk mitigation measures that when implemented, could improve safety. This work has value as a reference and guide for the safe development of offshore wind power.
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篇名 Assessment and Countermeasures for Offshore Wind Farm Risks Based on a Dynamic Bayesian Network
来源期刊 环境保护(英文) 学科 医学
关键词 BAYESIAN Network OFFSHORE Wind FARM Risk ASSESSMENT COUNTERMEASURES
年,卷(期) 2018,(4) 所属期刊栏目
研究方向 页码范围 368-384
页数 17页 分类号 R73
字数 语种
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研究主题发展历程
节点文献
BAYESIAN
Network
OFFSHORE
Wind
FARM
Risk
ASSESSMENT
COUNTERMEASURES
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研究去脉
引文网络交叉学科
相关学者/机构
期刊影响力
环境保护(英文)
月刊
2152-2197
武汉市江夏区汤逊湖北路38号光谷总部空间
出版文献量(篇)
956
总下载数(次)
0
总被引数(次)
0
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