A Wind-PV Aggregated Output Scenarios Generating Method Based on K+AP Algorithm

In the context of energy interconnection, with the dramatic increase of grid-connected photovoltaic (PV) and wind power, to solve the problem of large differences in wind power and PV power generation models, through the data-driven, this paper proposes a wind-PV aggregated output scenarios generation model, which characterizes the scenario output uniformly as the sum of 'horizontal output + fluctuating output by factor analysis and forms the aggregated output matrix. Then adopts the combination of K-means and affinity propagation (AP) algorithm to cluster analyze the high-dimensional data. Take the measured data from a region in Germany as an example, this paper compares with K-means and AP to verify the superiority of the proposed algorithm under 3 indicators.