Research on distribution network expansion planning based on load feature library and load simultaneous rate

With the growth of electric load and the increase of load density, the distribution network planning has become more and more complicated. The complexity of distribution network expansion planning is highlighted by its large scale, uncertainty, lack of refinement, factors and extensive areas involved, and the distribution network planning relying only on the planning experience of planning workers is far from meeting the requirements of modern distribution network planning. At present, most of the distribution network expansion planning is based on the load forecast of the area, but the traditional load forecasting methods are difficult to make accurate forecasts for situations where the load change pattern is complex. In this paper, load forecasting is performed by artificial intelligence based on load feature library and load simultaneous rate, and load characteristics are optimized to improve the accuracy of load forecasting, which is helpful for distribution network expansion planning. Load data from relevant areas are selected for experiments to verify the accuracy of the adopted method.