新型垂直轴风力发电机的协同进化
Toward the Coevolution of Novel Vertical-Axis Wind Turbines
摘要：
生产可再生和可持续能源是人类目前面临的最重要挑战之一。风能对世界能源供应结构的贡献越来越大，但距离充分发挥其潜力还有很长的路要走。在本文中，我们研究了使用人工进化来设计垂直轴风力涡轮机原型，这些原型在风扇产生的风力条件下进行了物理实例化和评估。首先，传统的进化算法是用来探索一个单一的风力涡轮机的设计空间，后来的合作协同进化算法是用来探索一个阵列的风力涡轮机的设计空间。人工神经网络在整个过程中被用作代理模型来辅助学习，并被发现可以减少达到更高的空气动力学效率所需的制造数量。与其他方法不同，例如计算流体动力学模拟，不使用数学公式，也不进行模型假设。
英文摘要：
The production of renewable and sustainable energy is one of the most important challenges currently facing mankind. Wind has made an increasing contribution to the world's energy supply mix, but still remains a long way from reaching its full potential. In this paper, we investigate the use of artificial evolution to design vertical-axis wind turbine prototypes that are physically instantiated and evaluated under fan generated wind conditions. Initially a conventional evolutionary algorithm is used to explore the design space of a single wind turbine and later a cooperative coevolutionary algorithm is used to explore the design space of an array of wind turbines. Artificial neural networks are used throughout as surrogate models to assist learning and found to reduce the number of fabrications required to reach a higher aerodynamic efficiency. Unlike in other approaches, such as computational fluid dynamics simulations, no mathematical formulations are used and no model assumptions are made.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
