A Two-Stage Scenario Generation Method for Wind- Solar Joint Power Output Considering Temporal and Spatial Correlations

Abstract

The output of wind and photovoltaic power has strong randomness and volatility. The current output model of wind and solar combined power generation systems is not accurate, and it is difficult to effectively characterize the complex temporal and spatial dependence of the active power of wind and photovoltaic power. For this reason, based on the Copula theory, this paper proposes a two-stage wind-solar joint output scenario generation method considering the temporal and spatial correlations. In the first stage, Copula model of HNAC structure was used to construct the output correlation between wind farms and photovoltaic power stations, as well as the output complementarity between wind power and photovoltaic power. Then, in the second stage, the Markov chain-based Copula model is used to consider the time series correlation of wind power and photovoltaic output. Meanwhile, the fluctuation characteristics of wind power and photovoltaic power under different output levels are considered. Finally, the Monte Carlo method is used to iteratively simulate a large number of wind and photovoltaic output sequences, and clustering generates typical scenes of wind and photovoltaic output. Simulation verification shows that the method can accurately reproduce the temporal and spatial correlation of wind power and photovoltaic output, and improve the accuracy of scene simulation of wind-solar joint power output.