Mixed Gaussian Models for Modeling Fluctuation Process Characteristics of Photovoltaic Outputs

In order to model fluctuation process characteristics of photovoltaic (PV) outputs, this paper proposes a novel mixed Gaussian model with the expectation maximization (EM) algorithm. Firstly, random components of PV outputs are obtained through computing the difference between the measured data of PV output and its theoretical outputs. Secondly, the EM algorithm is used to determine the weight of different Gaussian distribution functions. Finally, the mixed Gaussian model is obtained by linearly superimposing these Gaussian functions with the weight. Based on the simulation results on the measured data in Xichang City, China, the effectiveness of the proposed model is verified. Furthermore, this model has proven to be significantly better than other traditional models including t location-scale (TLS) distribution model.