摘要
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.
作者
赵书强
王皓
张辉
王枭枭
刘金山
ZHAO Shuqiang;WANG Hao;ZHANG Hui;WANG Xiaoxiao;LIU Jinshan(School of Electrical and Electronic Engineering,North China Electric Power University,Baoding 071003,China;State Grid Qinghai Electric Power Company,Xining 810008,China)
出处
《智慧电力》
北大核心
2020年第7期52-58,87,共8页
Smart Power
基金
国家重点研发计划资助项目(2017YFB0902200)
国家电网公司科技项目资助(5228001700CW)。
关键词
光伏出力模型
风电出力模型
短期相依
同期相依
连续状态马尔科夫链
COPULA函数
photovoltaic output model
wind farm output model
temporal dependence
contemporaneous dependence
continuous state Markov chain
Copula function