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Techno-economic optimisation of offshore wind farms based on life cycle cost analysis on the UK

机译:基于英国生命周期成本分析的海上风电场技术经济优化

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In order to reduce the cost of energy per MWh in wind energy sector and support investment decisions, an optimisation methodology is developed and applied on Round 3 offshore zones, which are specific sites released by the Crown Estate for offshore wind farm deployments, and for each zone individually in the UK. The 8-objective optimisation problem includes five techno-economic Life Cycle Cost factors that are directly linked to the physical aspects of each location, where three different wind farm layouts and four types of turbines are considered. Optimal trade-offs are revealed by using NSGA II and sensitivity analysis is conducted for deeper insight for both industrial and policy-making purposes. Four optimum solutions were discovered in the range between 1.6 pound and 1.8 pound billion; the areas of Seagreen Alpha, East Anglia One and Hornsea Project One. The highly complex nature of the decision variables and their interdependencies were revealed, where the combinations of site-layout and site-turbine size captured above 20% of total Sobol indices in total cost. The proposed framework could also be applied to other sectors in order to increase investment confidence. (C) 2018 The Author(s). Published by Elsevier Ltd.
机译:为了降低风能领域每兆瓦时的能源成本并支持投资决策,开发了一种优化方法,并将其应用于第3轮近海区域,这是Crown Estate发布的用于海上风电场部署的特定站点,每个站点在英国单独设置区域。 8目标优化问题包括与每个位置的物理方面直接相关的五个技术经济生命周期成本因素,其中考虑了三种不同的风电场布局和四种类型的涡轮机。通过使用NSGA II可以找到最佳的取舍,并进行敏感性分析以更深入地洞察工业和政策制定目的。发现了四个最佳解决方案,范围在1.6磅至1.8磅十亿之间。 Seagreen Alpha,East Anglia One和Hornsea Project One的区域。揭示了决策变量的高度复杂性及其相互依赖性,其中站点布局和站点涡轮大小的组合占总成本的总Sobol指数超过20%。拟议的框架也可适用于其他部门,以增加投资信心。 (C)2018作者。由Elsevier Ltd.发布

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