计及相关性的风电场和光伏电站时序出力模型研究

Wind Farm and Photovoltaic Power Station Output Time Series Model Considering Correlation

在大规模风光并网时,采用具有相关性的风光时序数据进行系统可靠性评估能够更好模拟系统的运行状态,有利于提高可靠性评估的准确性和实用性。基于混合Copula函数和马尔科夫过程相关理论,建立了一种用于可靠性评估的计及相关性的风光时序出力模型。首先,通过区分光伏出力序列中的规律性与随机性特征,提取出光伏出力的随机分量;然后将风光时序相关性模型分解为风电出力时序模型、光伏出力时序模型以及风光出力的时序相依模型3部分。最后,通过比利时瓦垄地区的实测数据对上述模型进行了验证。

When large-scale wind and photovoltaic power grid-connected,the system reliability evaluation using relevant wind and photovoltaic time series data can better simulate the operation status of the system,which is conducive to improve the accuracy and practicability of the system reliability evaluation. Based on mixed-Copula function and Markov process theory,a time series power output model for reliability assessment and correlation is established. Firstly,the random component of photovoltaic output is extracted by distinguishing the regularity and randomness of photovoltaic output series. Then,the time series correlation model of wind power output is decomposed into three parts: the time series model of wind power output,the time series model of photovoltaic output and the time series dependence model of wind-pv power output. Finally,the above models are validated by the measured data in Walong area of Belgium.