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Optimizing the number and locations of turbines in a wind farm addressing energy-noise trade-off: A hybrid approach

机译：优化风电场中涡轮机的数量和位置以解决能量噪声折衷：混合方法

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Micro-siting is an optimal way of placing turbines inside a wind farm while considering various design objectives and constraints. Using a well-established Jensen wake model and ISO-9613-2 noise calculation, this study performs a wind farm layout optimization based on a multi-objective trade-off between minimization of the noise propagation and maximization of the energy generation, A novel hybrid methodology is developed which is a combination of probabilistic real-binary coded multi-objective evolutionary algorithm and a newly proposed deterministic gradient based non-dominated normalized normal constraint method, Based on the Inverted Generational Distance metric, the performance of the proposed method is found to be better than the conventional normalized normal constraint method or the concerned evolutionary method alone, Moreover, in contrast to the previous studies, the generated non-dominated front is capable of providing a trade-off between various alternative energy-noise solutions, along with an additional information about the corresponding turbine numbers and their optimal location coordinates. As a result, the decision maker can choose from different competing wind turbine layouts based on existing noise and other standard regulations. (C) 2016 Elsevier Ltd. All rights reserved.
机译：考虑到各种设计目标和约束条件时，微选址是将涡轮机放置在风电场内部的最佳方法。本研究使用完善的Jensen尾流模型和ISO-9613-2噪声计算，基于最小化噪声传播与最大能量产生之间的多目标权衡，进行了风电场布局优化，这是一种新型混合动力结合概率实数二进制编码多目标进化算法和新提出的基于确定性梯度的非支配归一化法向约束方法的组合方法，基于逆生成距离度量，发现该方法的性能优于传统的归一化法向约束方法或单独的相关进化方法。此外，与以前的研究相比，生成的非支配前沿能够在各种替代性能源噪声解决方案之间进行权衡。有关相应涡轮机号及其最佳位置坐标的其他信息。因此，决策者可以根据现有的噪声和其他标准法规，从不同的竞争性风力涡轮机布局中进行选择。 （C）2016 Elsevier Ltd.保留所有权利。

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