TY - CONF JO - Innovative Smart Grid Technologies (ISGT Europe), 2012 3rd IEEE PES International Conference and Exhibition on TI - Identification of Gaussian mixture model using Mean Variance Mapping Optimization: Venezuelan case T2 - Innovative Smart Grid Technologies (ISGT Europe), 2012 3rd IEEE PES International Conference and Exhibition on IS - SN - 2165-4816 VO - SP - 1 EP - 6 AU - Gonzalez-Longatt, F. M. AU - Rueda, J. L. AU - Erlich, I. AU - Bogdanov, D. AU - Villa, W. Y1 - 14-17 Oct. 2012 PY - 2012 KW - Gaussian mixture model KW - Load modeling KW - Optimization KW - Probabilistic logic KW - Substations KW - Gaussian mixture model KW - load profile KW - mean-variance mapping optimization KW - probability distribution function VL - JA - Innovative Smart Grid Technologies (ISGT Europe), 2012 3rd IEEE PES International Conference and Exhibition on DO - 10.1109/ISGTEurope.2012.6465672 AB - The characterization of random load behavior has been largely attempted through statistics-based model fitting. Remarkably, the use of Gaussian mixture model (GMM) has proven to be adequate to tackle the heterogeneity and variability of the statistical distribution of loads. In this paper, an application of the Mean-Variance Mapping Optimization (MVMO) algorithm to the identification of the parameters of GMMs, is presented. The feasibility of the proposed identification approach is demonstrated using historical data records from the Venezuelan transmission system portion that covers the Paraguaná Peninsula. ER -