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Integrated optimization of offshore wind farm layout design and turbine opportunistic condition-based maintenance

机译:海上风电场布局设计和涡轮机机会状态维护的综合优化

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摘要

A two-stage optimization model has been developed for an offshore wind farm that integrates layout design and turbine maintenance policy-making. In Stage 1, first, the optimal development of the offshore wind resource aims to maximize the wind energy production by seeking the optimal turbine layout under uncertainty of wind conditions, in which the optimal number of turbines N and their productive placement are determined. Then, the locations of N turbines are further optimized for maximal energy production. Due to the unique maintenance challenges for offshore wind farm, in Stage 2, we develop computational tools for a novel opportunistic condition-based maintenance policy, in which the periodic inspection intervals are chosen to ensure the reliable energy production with limited maintenance costs. In this study, probabilistic models are built for stochastic wind speeds and directions. We apply Monte Carlo simulation for sampling wind data from the wind probabilistic models considering multiple seasonal scenarios. The algorithm efficiency of the two-stage optimization framework is demonstrated based on the results of a case of wind farm development along the New Jersey coast.
机译:已经为海上风电场开发了一个两阶段的优化模型,该模型将布局设计和涡轮机维护决策结合在一起。在第一阶段,首先,海上风能的最佳开发旨在通过在风况不确定的情况下寻求最佳的风机布置来最大化风能产量,其中确定最佳的风机数量N及其生产位置。然后,进一步优化N个涡轮的位置,以最大程度地产生能量。由于海上风电场面临独特的维护挑战,因此在第2阶段,我们开发了一种用于基于机会条件的新型维护策略的计算工具,其中选择了定期检查间隔以确保可靠的能源生产且维护成本有限。在这项研究中,建立了随机风速和风向的概率模型。考虑到多个季节情况,我们将蒙特卡洛模拟应用于从风概率模型中采样风数据。基于新泽西州海岸风电场开发案例的结果证明了两阶段优化框架的算法效率。

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