Research on the Construction of a Visualized Urban Power Supply Capacity Map with improved Power Grid Load Forecasting Methods

This article conducts in-depth research on the construction of urban power supply capacity maps, and achieves real-time display and prediction of power supply capacity through grid load prediction algorithms and GIS visualization technology. Firstly, a distribution network line model library was established to obtain accurate distribution of power supply capacity through multi-source data fusion technology. Secondly, LDI and neural network methods are used to analyze and predict power grid load data. Finally, the power supply capacity data is presented in a vivid and comprehensive manner through the GIS visualization platform, providing an intuitive and comprehensive view, enabling users to quickly obtain information on the power supply capacity of the regional distribution network. These research results not only have important value for decision-making in the power grid, but also provide useful reference information for government departments to support urban power planning and development.