风速时序仿真模型及其在发电系统可靠性评估中的应用（英文）

A Wind Speed Time Series Simulation Method and Its Application in Reliability Assessment of Generating Systems

风速模拟在风电领域相关研究中具有重要的应用。基于多项式正态变换和连续状态马尔科夫链技术,提出了一种时序风速的模拟方法。该方法首先利用多项式正态变换方法将原始数据变换为服从正态分布的数据;然后利用连续状态马尔科夫链描述变换后数据的随机波动过程;最后,通过正态逆变换获得模拟产生的风速数据。实际风速数据验证表明,模型能够较好地保持原始风速数据的概率分布特性和短期相依特性。将该模型应用于IEEE-RTS可靠性测试系统,结果表明模型可进行含风能的电力系统可靠性评估。

Simulating wind speed data has important implications in wind studies.A methodology to generate wind speed time series is provided based on polynomial normal transformation （PNT） and continuous state Markov chain （CSMC）. The method firstly transforms the historical data into normal-followed data using PNT, next describes the stochastic process of the transformed data using the CSMC, and finally obtains the simulated wind speed series by performing the back-transformation of synthetic time series into the initial domain. Case studies are used to illustrate the capabilities of the proposed method .The results prove that the method can offer satisfactory fit for both probability distribution and temporal dependence. Case studies on a standard IEEE reliability test system （IEEE-RTS） have verified the applicability and effectiveness of the proposed model in evaluating the reliability performance of wind farms.