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Comprehensive modeling and parameter identification of wind farms based on wide-area measurement systems

机译:基于广域测量系统的风电场综合建模与参数辨识

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摘要

With intermittence and stochastics of wind power largely introduced into power systems, power system stability analysis and control is in urgent need of reliable wind farm models. Considering the superiority of wide-area measurement systems, this paper develops a novel methodology for practical synchrophasor measurement-based modeling and parameter identification of wind farms. For the sake of preserving basic structural characteristics and control patterns simultaneously, a comprehensive wind farm model is constructed elaborately. To improve the efficiency of the identification procedure,dominant parameters are classified and selected by trajectory sensitivity analysis. Furthermore, an improved genetic algorithm is proposed to strengthen the capability of global optimization. The test results on the WECC benchmark system and the CEPRI 36-bus system demonstrate the effectiveness and reliability of the proposed modeling and identification methodology.
机译:随着电力电力的间歇性和随机电量引入电力系统,电力系统稳定性分析和控制迫切需要可靠的风电场模型。考虑到广域测量系统的优越性,本文开发了一种基于实际同步素测量的模拟和风电场参数识别的新方法。为了同时保留基本结构特征和控制模式,精心构建综合风电场模型。为了提高识别程序的效率,通过轨迹敏感性分析来分类和选择显性参数。此外,提出了一种改进的遗传算法来增强全局优化的能力。 WECC基准系统和CEPRI 36总线系统的测试结果展示了所提出的建模和识别方法的有效性和可靠性。

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