Abstract：The randomness, volatility and intermittent nature of new energy resources bring troubles to power system planning. A reasonable description of how wind power and photovoltaic output behave and generating typical output scene is a common method for new energy planning. A method for generating typical scene of relevant wind power and photovoltaic output is proposed. This paper firstly fits a large number of sample data based on kernel density estimation, and performs fitting and pre-test to obtain a kernel density estimation expression of wind and photovoltaic power output. This paper builds a variety of combined distribution models of wind and photovoltaic power based on Copula functions, and then judges the fitness of each model. The Kendall and Spearman correlation coefficients of each model are considered to select the optimal Copula function as wind power, photovoltaic joint probability distribution. Finally, the annual power output of wind and photovoltaic power is generated based on the optimal Copula joint probability distribution. Case analysis shows that the simulation results of annual output of wind and photovoltaic power meets their relevance, and has higher accuracy in wind and photovoltaic power output in the reaction. There must be a certain reference value for the reliability analysis of power system and grid planning.
宋宇, 李涵. 基于核密度估计和Copula函数的风、光出力场景生成[J]. 电气技术, 2022, 23(1): 56-63.
SONG Yu, LI Han. Typical scene generation of wind and photovoltaic power output based on kernel density estimation and Copula function. Electrical Engineering, 2022, 23(1): 56-63.
2022, Vol. 23 
