陈文进,王小仲,张思,甘雯,沈诚亮,顾伟康,邱剑
CHEN Wenjin,WANG Xiaozhong,ZHANG Si,GAN Wen,SHEN Chengliang,GU Weikang,QIU Jian

• 1:国网浙江省电力有限公司
• 2:国网浙江省电力有限公司湖州供电公司
• 3:浙江大学电气工程学院

摘要(Abstract)：

以风电为代表的新能源具有波动性和间歇性等特性，因此风电功率不确定性强且功率预测存在一定的预测误差。为准确把握功率预测误差分布的差异化，基于Copula函数提出了一种考虑功率-误差相关性的风电功率概率预测模型。首先，构建基于提示学习的风电功率点预测模型，预判风电功率的变化趋势。然后，为准确分析预测误差分布情况，采用Copula函数分析风电功率预测与预测误差之间的相关性，针对各个功率预测值建立对应的预测误差概率密度函数，得到一定置信度下风电功率预测值可能发生波动的区间范围。最后，验证所提风电功率概率预测模型的有效性。
New energy sources, such as wind power, are characterized by volatility and intermittency, leading to significant uncertainty in wind power output and errors in power forecasting. To accurately capture the differentiated distribution of power forecasting errors, a copula-based probabilistic wind power forecasting model considering power error correlation is proposed. First, a wind power point forecasting model is developed using prompt learning to predict the trends in wind power. Subsequently, a copula is employed to analyze the correlation between wind power forecasting and forecasting errors, enabling the establishment of probability density functions for forecasting errors corresponding to each forecasting value. This method determines the range of potential fluctuations in wind power forecasting within a given confidence level. Finally, the proposed probabilistic wind power forecasting model is validated, demonstrating its effectiveness.

关键词(KeyWords)： 风电功率;提示学习;相关性;Copula函数;功率概率预测
wind power;prompt learning;correlation;copula;probabilistic power forecasting

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金联合基金(U22B2098);; 国网浙江省电力有限公司科技项目(B311UZ23000B)

作者(Author): 陈文进,王小仲,张思,甘雯,沈诚亮,顾伟康,邱剑
CHEN Wenjin,WANG Xiaozhong,ZHANG Si,GAN Wen,SHEN Chengliang,GU Weikang,QIU Jian

DOI: 10.19585/j.zjdl.202507006

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