Equivalent Modeling of Photovoltaic Power Plant Based on Factor Analysis and Correlation Clustering

Abstract

The equivalent model of photovoltaic (PV) power plant can greatly improve the model simulation speed on the basis of satisfying the simulation accuracy. However, in equivalent modeling of PV power plant, there are strong correlations and subjectivity between the selected initial variables, which will cause inaccurate equivalent results. Therefore, this paper proposes an equivalent modeling method of PV power plant based on factor analysis and correlation clustering. First, the factor analysis is used to reduce the dimensions of initial variables to eliminate the correlations between clustering indexes. The factor rotation and factor scores are adapted to mine the actual physical meaning of data, extracting the operation states of PV units, and eliminating the subjectivity of clustering indexes. Second, the correlation analysis and significance test are applied to analyze the extracted operation state indexes to obtain the correlations between PV units for clustering. Third, by the contour visualization, the correlations between PV units are qualitatively analyzed and the rationality of clustering results is judged. Finally, the equivalent parameters are calculated based on clustering results to establish the equivalent model of the PV power plant. The simulation results show that the proposed equivalent modeling method not only improves the simulation speed but also fit the simulation accuracy as well. The adaptability of the equivalent modeling method under different working conditions is also verified. The established equivalent model can be used to analyze the interaction between the PV power plant and power grid as well as the power system analysis with large-scale new energy, which is practical and popularized.

Keywords

• Correlation clustering
• contour visualization
• equivalent modeling
• factor analysis
• PV power plant