Scenarios Analysis Method Based on Wind and Photovoltaic Power Output Correlation

Abstract

In the planning and operation of power system, typical scenario generation is a common method to deal with the uncertainty of wind and photovoltaic power output. In this paper, adaptive prediction method is used to build the output prediction error model of wind and photovoltaic power output. Next, Copula function is used to build the correlation model of wind and photovoltaic power output. Then, the improved Latin hypercube sampling is used to generate a large number of initial scenarios in the correlation model. Further, the improved K-means clustering algorithm is used to reduce initial scenarios, and generate typical scenarios of wind-solar joint power output. Finally, the example shows that the typical scenarios generated by the scenario analysis method can well describe actual output under different condition. Consequently, the can well fit the historical data of wind-solar joint output, and has important feasibility and practical value.