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A novel reliability evaluation method of AC/DC hybrid power system with the injection of wind power

机译:一种新颖的AC / DC混合动力系统的可靠性评估方法,其注入风电

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With the rapid development of HVDC projects and renewable energy, reliability of AC/DC hybrid power system with wind power draws more and more attention. To depict the uncertainty of wind power, this paper proposes the wind power BP neural network model to fit the probability distribution of actual wind speed. Compared with traditional wind power models such as Weibull distribution model, the BP neural network model is closer to the actual probability distribution of wind speed according to numerical results. By using Monte Carlo method, the AC/DC hybrid system states are obtained. Then considering the interaction between AC and DC system, a novel minimum load shedding model of hybrid system with HVDC is proposed. IEEE-RTS 96 system is testified with actual Northern China wind data, which illustrates a more accurate wind power modeling as well as a comprehensive reliability evaluation on AC/DC hybrid power system integrated with wind power.
机译:随着HVDC项目的快速发展和可再生能源,AC / DC混合动力系统的可靠性越来越受到越来越多的关注。为了描绘风力的不确定性,本文提出了风电BP神经网络模型,以适应实际风速的概率分布。与诸如Weibull分布模型的传统风电模型相比,BP神经网络模型根据数值结果更接近风速的实际概率分布。通过使用Monte Carlo方法,获得了AC / DC混合系统状态。然后考虑AC和DC系统之间的相互作用,提出了具有HVDC的混合系统的新型最小载荷脱落模型。 IEEE-RTS 96系统经过实际的北方风数据作证,说明了一种更准确的风电建模以及与风电集成的AC / DC混合动力系统的全面可靠性评估。

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