Research on Wind-Photovoltaic Output Power Aggregation Method Considering Correlation

In order to improve the computational efficiency of power system time series simulation, the redundancy of wind power and photovoltaic time series data should be reduced. At present, the time series data of wind-photovoltaic are aggregated separately, wind and pv correlation is not involved, reducing the accuracy and reliability of high-proportion renewable energy power system simulation. For this reason, This paper presents a aggregation method involving wind power and photovoltaic correlation. Based on wind and photovoltaic power historical data, firstly, based on kernel density estimation method and Copula theory, generate the wind-photovoltaic kernel density function and the joint probability density function, by sampling the joint probability density function to obtain N groups of typical daily curves. Take a provincial power grid as an example, a comparative analysis was made between the proposed wind-photovoltaic correlation aggregation method and the separate wind-photovoltaic aggregation method, The results show that the aggregation series can not only accurately reflect the characteristics of original wind-photovoltaic output power, but also maintain the correlation between wind-photovoltaic output power, which has certain engineering application value.