连续状态马尔科夫链风速模型及其在风电系统可靠性评估中的应用

CSMC Model for Wind Speed and Its Application in Reliability Evaluation of Power System Containing Wind Energy

基于连续状态马尔科夫链模型提出一种时序风速模拟模型。该模型利用Box-Cox技术将风速序列变换为服从正态分布的序列,进而在多维正态概率空间内构造变换数据的连续状态马尔科夫链模型。在此基础上,利用Box-Cox反变换将正态序列变换为风速序列,进而得到时序风速的连续状态马尔科夫链。采用实测风速数据验证本文模型的有效性,结果表明:本文提出的模型可保持原风速的概率分布和自相关特性。采用IEEE-RTS可靠性测试系统验证本文模型的应用性,结果表明:本文模型可用于含风能的电力系统发电可靠性评估。

A time series wind speed model is presented based on continuous state markov chain （CSMC） in this paper.The recorded wind speed time series is transformed into that in the normal distribution domain using Box-Cox technique,and then a CSMC model of transformed data is constructed in multi-dimensional normal domain.In addition,normal distributed data is transformed into wind speed data by using of the Box-Cox back-transformation,therefore a CSMC model of wind speed time series is built.The validity of proposed model is testified by measured wind speed data,which shows that the model can preserve the probability distribution and autocorrelation characteristics of original wind speed.The applicability of the proposed model is also verified on the IEEERTS test system,which shows that it can be used to evaluate the reliability of power systems with wind energy.