Short term wind power scenarios forecast based on multivariate normal distribution

2nd International Symposium on Resource Exploration and Environmental Science

生态环境科学

Liu, Shuai^1 ; Zhu, Yongli^1 ; Gao, Jiacheng^1 ; Zhang, Ke^1

North China Electric Power University, Baoding, China^1

关键词: Covariance function;    Different time scale;    Dynamic scenarios;    Multi-variate normal distributions;    Power fluctuations;    Probability modeling;    Wind power forecast;    Wind power penetration;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/170/4/042038/pdf
DOI  :  10.1088/1755-1315/170/4/042038

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

According to the fact that the increase of wind power penetration rate causes the influence of wind power's randomness and fluctuation on the power grid, the single short-term wind power point prediction often cannot meet the needs of power grid risk assessment and decision-making. In this paper, we first calculate the theoretical probability model of each wind power forecast box by the end function in MATLAB, and then use the exponential covariance function expression to determine the best covariance matrix corresponding to the dynamic scenarios, and determine the multivariate normal distribution model of wind farm output obedience at multiple connected moments; For each predicted moment of the wind power point prediction value of the wind belongs to the prediction box, we direct sample random vector which obey multivariate normal distribution to form the wind power dynamic scenario. After a simulation experiment on a real wind farm, the results show that the scenario set considering wind power fluctuation at different time scales can cover the measured wind power curve and the reliability of the method is proved.