Space Load Forecasting Considering Distributed Energy and Electric Vehicles

Abstract

Compared with the traditional load forecasting, the spatial load forecasting pays more attention to the load distribution in a certain local area or space, so it can better determine the selection and spatial layout of the electrical equipment, which plays an important role in the planning of the urban power grid. The rapid development of distributed energy and electric vehicles has broken the original law of urban load development, and makes the urban spatial load distribution more complex. The original load forecasting method based time series may bring large error to the prediction results, which is not conducive to the economy and reliability of urban power grid planning. Because the least squares support vector machine has strong nonlinear mapping ability, this paper establishes a LS-SVM based spatial load forecasting model for distributed and electric vehicle charging load based on the analysis of the core influence factors of various kinds of loads. Finally, a practical example in a certain area of central China shows the effectiveness of the proposed method.