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Time Scale Analysis and Synthesis of Deterministic and Stochastic Wind Energy Conversion Systems

机译:确定性和随机风能转换系统的时标分析和综合

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The threat of climate change and diminishing fossil fuels demands nothing short of an energy revolution, a transformation which is already underway as renewable energy markets exhibit enormous and steady growth. This paper presents design of optimal control schemes for Wind Energy Conversion Systems (WECS) based on a time scale technique. The dynamics governing the mechanical components of a variable speed wind turbine are decoupled to bring about model order reduction, facilitating computationally efficient control schemes. Linear Quadratic Regulators (LQR) and Linear Quadratic Gaussian (LQG) controllers for deterministic and stochastic WECS models are discussed at length. Comparisons were made between controllers for the reduced order and full order systems. The results manifest the effectiveness of the proposed method, which provides comparable control while reducing model order and increasing computational efficiency.
机译:气候变化和化石燃料的减少所带来的威胁,无非是一场能源革命,随着可再生能源市场呈现出巨大而稳定的增长,这种变革已经在进行。本文提出了一种基于时标技术的风能转换系统(WECS)最优控制方案的设计。将控制变速风力涡轮机机械部件的动力学解耦以减少模型阶数,从而简化了计算效率高的控制方案。详细讨论了用于确定性和随机WECS模型的线性二次调节器(LQR)和线性二次高斯(LQG)控制器。对降阶系统和全阶系统的控制器进行了比较。结果证明了所提方法的有效性,该方法在降低模型阶数和提高计算效率的同时提供了可比的控制。

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