摘要
针对风电功率预测误差估计方法中混合高斯分布拟合法和特征值提取估计法这两种适用范围较广的风电功率预测误差估计方法,详细介绍其原理和误差估计流程,利用实际风电场数据对两种方法进行算例验证,并根据计算结果,针对两种方法下的估计区间对储能容量配置的影响进行对比研究,为工程应用时的方法选取提供参考。同时,为了兼顾误差估计区间的有效性和经济性,有效指导风电场储能系统的容量配置,在高斯混合模型的基础上对风电功率预测误差进行状态划分,结合马尔可夫模型,提出一种MM-GMM优化预测误差区间估计算法并对其进行算例验证。
Aiming at two common wind power forecast error estimation methods,that is,the Gaussian mixture distribution fitting method and the eigenvalue extraction method,the principle and process of these two methods are introduced in detail.Moreover,these two methods are verified by the actual wind farm data,and the estimation intervals of two methods are compared according to the impact on energy storage capacity configuration.In order to give consideration to the accuracy and validity of error estimation interval and guide the configuration of energy storage system effectively,based on Gaussian mixture model(GMM)and combined with Markov model(MM),an MM-GMM based optimized forecast error interval estimation algorithm is proposed and verified.
作者
蒋艾町
李小雨
夏雪
李嘉逸
Jiang Aiting;Li Xiaoyu;Xia Xue;Li Jiayi(CPECC Southwest Electric Power Design Institute Co.,Ltd.,Chengdu 610021,Sichuan,China)
出处
《四川电力技术》
2021年第2期43-47,94,共6页
Sichuan Electric Power Technology
关键词
风电功率预测误差估计
储能容量配置
混合高斯分布
特征值提取
马尔可夫模型
wind power forecast error estimation
energy storage capacity configuration
Gaussian mixture distribution
eigenvalue extraction
Markov model
