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A Response Surface-Based Cost Model for Wind Farm Design

机译：基于响应面的风​​电场设计成本模型

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摘要

A Response Surface-Based Wind Farm Cost (RS-WFC) model is developed for the engineering planning of wind farms. The RS-WFC model is developed using Extended Radial Basis Functions (E-RBF) for onshore wind farms in the U.S. This model is then used to explore the influences of different design and economic parameters, including number of turbines, rotor diameter and labor cost, on the cost of a wind farm. The RS-WFC model is composed of three components that estimate the effects of engineering and economic factors on (i) the installation cost, (ii) the annual Operation and Maintenance (O&M) cost, and (iii) the total annual cost of a wind farm. The accuracy of the cost model is favorably established through comparison with pertinent commercial data. The final RS-WFC model provided interesting insights into cost variation with respect to critical engineering and economic parameters. In addition, a newly developed analytical wind farm engineering model is used to determine the power generated by the farm, and the subsequent Cost of Energy (COE). This COE is optimized for a unidirectional uniform "incoming wind speed" scenario using Particle Swarm Optimization (PSO). We found that the COE could be appreciably minimized through layout optimization, thereby yielding significant cost savings.
机译：针对风电场的工程规划，开发了基于响应面的风​​电场成本（RS-WFC）模型。 RS-WFC模型是使用扩展的径向基函数（E-RBF）为美国陆上风电场开发的。然后，该模型用于探索不同设计和经济参数（包括涡轮机数量，转子直径和人工成本）的影响，但要以风电场为代价。 RS-WFC模型由三个部分组成，这些部分估计了工程和经济因素对（i）安装成本，（ii）年度运营和维护（O＆M）成本以及（iii）每年的总成本的影响。风电场。通过与相关的商业数据进行比较，可以有利地确定成本模型的准确性。最终的RS-WFC模型提供了有关关键工程和经济参数方面的成本变化的有趣见解。此外，新开发的分析型风电场工程模型用于确定风电场产生的功率以及随后的能源成本（COE）。使用粒子群优化（PSO）针对单向均匀“传入风速”方案对该COE进行了优化。我们发现可以通过布局优化将COE显着最小化，从而节省大量成本。

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  • 来源
    《Energy Policy》 |2012年第3期|p.538-550|共13页
  • 作者

    Jie Zhang; Souma Chowdhury; Achille Messac; Luciano Castillo;

  • 作者单位

    Department of Mechanical, Aerospace, and Nuclear Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, United States;

    Department of Mechanical, Aerospace, and Nuclear Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, United States;

    Department of Mechanical and Aerospace Engineering, Syracuse University, Syracuse, NY 13244, United States;

    Mechanical Engineering Department, Texas Tech University, Lubbock, TX 79409, United States;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    cost of energy; optimization; wind farm;

    机译：能源成本;优化;风电场;

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