面向海上风电的GARCH残差耦合Copula函数的风浪联合时序场景生成方法OA
A Method for Generating Joint Wind-wave Time Series Scenarios for Offshore Wind Power Using GARCH Residual-based Copula Function Coupling
风速与浪高均会影响海上风电出力的安全性与稳定性,现有海上风电相关研究对风浪协同作用的考虑尚不充分.尤其是台风过境时,风浪剧烈变化对风电出力的影响需要精准的建模方法.为此,提出一种融合统计建模与时序结构的风浪联合场景生成方法,有望捕捉风与浪的共变规律.首先针对台风场景使用风浪数据采用核密度估计法构建边缘分布函数.其次,基于GARCH模型按季节提取数据的波动特征,并构建标准化残差.最后对边缘分布函数与残差构建Copula函数簇联合分布,通过Kendall系数、Spearman系数及平均欧氏距离综合评价获取台风与不同季节最优Copula模型,随后引入AR(1)扰动生成具有时序性的联合场景,并采用K-medoids算法对场景聚类缩减并概率赋值.结果表明该方法适用台风与不同季节的风浪关系,通过Copula模型与AR时序机制,有效提升风浪场景时序性,可为强风浪波动下海上风电的安全稳定出力提供参考.
Wind speed and wave height both affect the safety and stability of offshore wind power output,while traditional studies on offshore wind power output have insufficient consideration of wind-wave coupling effects.In particular,during typhoon events,the drastic variation of wind and waves requires accurate modeling approaches.To address this,a wind-wave joint scenario generation method integrating statistical modeling and temporal structure is proposed to capture the covariation patterns of wind and waves.Firstly,for typhoon scenarios,the marginal distribution functions of wind and wave data are constructed using kernel density estimation.Secondly,based on the GARCH model,the seasonal fluctuation characteristics are extracted and standardized residuals are constructed.Finally,Copula function families are applied to fit the joint distribution of marginal functions and residuals.The optimal Copula model for typhoon and seasonal conditions is selected based on Kendall coefficient,Spearman coefficient,and mean squared Euclidean distance.An AR(1)perturbation structure is then introduced to generate temporally correlated joint scenarios,followed by K-medoids clustering and probability assignment.The results show that the proposed method is applicable to both typhoon and seasonal wind-wave relationships.By integrating Copula modeling and AR temporal mechanism,the temporal coherence of wind-wave scenarios is significantly improved,providing a valuable reference for safe and stable offshore wind power output under extreme wind-wave fluctuations.
朱志家;王海鑫;景锐;夏明超;杨俊友
沈阳工业大学电气工程学院,辽宁省 沈阳市 110870||厦门大学能源学院,福建省 厦门市 361102沈阳工业大学电气工程学院,辽宁省 沈阳市 110870厦门大学能源学院,福建省 厦门市 361102沈阳工业大学电气工程学院,辽宁省 沈阳市 110870沈阳工业大学电气工程学院,辽宁省 沈阳市 110870
信息技术与安全科学
风浪相关性Copula函数时序场景生成风浪时空分布
wind-wave correlationCopula functiontemporal scenario generationspatiotemporal distribution of wind and wave
《全球能源互联网》 2026 (3)
392-406,15
国家自然科学基金重点项目(52337003)国家自然科学基金青年项目(52306027)辽宁省科技计划联合计划项目(2023JH2/101700275). The Key Program of the National Nature Science Foundation(52337003)The Young Program of the National Nature Science Foundation(52306027)Liaoning Province Science and Technology Plan Joint Program Project(2023JH2/101700275).
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