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In order to improve the accuracy of theoretical energy loss calculation in low voltage distribution area (LV-area), this paper proposes a new prediction method based on variational mode decomposition (VMD) and particle swarm optimization (PSO) least squares support vector machine (LSSVM). Firstly, the main influencing factors of energy loss calculation in LV-area are determined by the grey correlation method, which reflects the data-driven characteristic of the method and ensures the objectivity of the prediction results and the generalization of the calculation model. Secondly, the trend component and fluctuation component are obtained by VMD of daily energy loss series in the LV-area. The variable set of main influencing factors of energy losses is used as the input variable of LSSVM, and the VMD result of the energy loss sequence is used as the output. The theoretical energy loss training and calculation model of LV-area is established. Compared with the traditional calculation model, this model has more accurate calculation accuracy by taking into account the frequency characteristics of energy losses in different frequency bands. PSO is used to optimize the parameters of LSSVM for the purpose of improving the accuracy of LSSVM. Finally, an example of 252 LV-area in a city in northern China is given to verify the validity of the proposed method. The results indicate that the proposed method generates more accurate results.

Energy Loss Calculation of Low Voltage Distribution Area Based on Variational Mode Decomposition and Least Squares Support Vector Machine