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Analysis of voltage stability uncertainty using stochastic response surface method related to wind farm correlation

机译:风电场相关性的随机响应面法分析电压稳定性不确定性

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Wind speed follows the Weibull probability distribution and wind power can have a significant influence on power system voltage stability. In order to research the influence of wind plant correlation on power system voltage stability, in this paper, the stochastic response surface method (SRSM) is applied to voltage stability analysis to establish the polynomial relationship between the random input and the output response. The Kendall rank correlation coefficient is selected to measure the correlation between wind farms, and the joint probability distribution of wind farms is calculated by Copula function. A dynamic system that includes system node voltages is established. The composite matrix spectral radius of the dynamic system is used as the output of the SRSM, whereas the wind speed is used as the input based on wind farm correlation. The proposed method is compared with the traditional Monte Carlo (MC) method, and the effectiveness and accuracy of the proposed approach is verified using the IEEE 24-bus system and the EPRI 36-bus system. The simulation results also indicate that the consideration of wind farm correlation can more accurately reflect the system stability.
机译:风速遵循威布尔概率分布,并且风能会对电力系统的电压稳定性产生重大影响。为了研究风电厂相关性对电力系统电压稳定性的影响,将随机响应面法(SRSM)应用于电压稳定性分析,建立了随机输入与输出响应之间的多项式关系。选择肯德尔秩相关系数来度量风电场之间的相关性,并利用Copula函数计算风电场的联合概率分布。建立包括系统节点电压的动态系统。动态系统的复合矩阵光谱半径用作SRSM的输出,而风速则基于风电场相关性用作输入。将该方法与传统的蒙特卡洛(MC)方法进行了比较,并使用IEEE 24-bus系统和EPRI 36总线系统验证了该方法的有效性和准确性。仿真结果还表明,考虑风电场相关性可以更准确地反映系统稳定性。

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