Customer Load Forecasting Method Based on the Industry Electricity Consumption Behavior Portrait

With the dramatic increase of energy demand and the continuous increase of power system operation pressure, higher requirements are put forward for the development of power grid planning and optimization operation. It is important for the refinement of distribution network planning to deeply extract the characteristics of user load. First, the process of load characteristic analysis method from the user level to the industry level is proposed, which achieves the division of electricity consumption patterns of various industries, thus building a panoramic portrait of industry electricity consumption behavior. Then, by expanding the information filled in by traditional customers, the feature vector of each user is extracted, and the users' industry electricity consumption patterns are used as the label. Therefore, a method for identifying the electricity consumption pattern of the customer based on the BB-stacking model fusion framework is proposed, which yields the preliminary forecast results of customer load based on the actual load accounting results of the customers. Finally, comparative simulations with different methods verify the effectiveness of the proposed algorithm, which can provide prominent guidance for the actual distribution network planning work.

Automated summary

The article proposes a method to refine distribution network planning by deeply extracting user load characteristics, and identifies customer load patterns by extracting feature vectors for each user and using customers' industry electricity consumption habits as labels. The effectiveness of the proposed algorithm is verified through comparative simulations with different methods, providing significant guidance for actual distribution network planning work.