User characteristic analysis-based multi-model load prediction method

Abstract

The invention discloses a user characteristic analysis-based multi-model load prediction method. The method comprises the steps of building a load prediction model based on different user characteristics by using a linear regression algorithm and a time sequence algorithm, building a data model through a specific data analysis algorithm to obtain multi-factor load prediction based on user characteristic analysis, and predicting line load values in the same period in the future through line load history data, micrometeorologic history data and regional GDP history data; and performing classification on line load data by utilizing a K-Means clustering algorithm, and classifying the line load data into a residential electricity consumption line, a commercial electricity consumption line and an industrial electricity consumption line according to electricity consumption types. According to the method, the difference among the lines different in electricity consumption type is fully considered, so that the model is more accurate; and the influence of multiple influence factors on loads is comprehensively considered, primary factors influencing the loads are found out by extracting primary components of the multiple influence factors, secondary factors are abandoned, and a primary influence factor-based prediction model is built by utilizing a data analysis algorithm.

Description

technical field [0001] The invention belongs to the technical field of power system planning and operation scheduling, and in particular relates to a multi-model load forecasting method based on user characteristic analysis. Background technique [0002] The power system has developed to this day and has become an indispensable and important link in national economic construction and people's life. The role of the power system is to provide continuous and good-quality electric energy to various users as economically as possible. The interruption and reduction of power supply will affect all sectors of the national economy, and even cause serious consequences. The size and characteristics of the load are extremely important for power system planning, energy resource balance, and power surplus and shortage adjustment. Compared with other commodities, electricity as a commodity has the biggest characteristic that it cannot be stored, that is to say, the production, transmissio...

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Problems solved by technology

However, due to the different types of electricity consumption in the jurisdiction of the power supply company, including residential electricity, commercial electricity, and industrial electricity, and the power load is affected by many factors, such as temperature, per capita income level, policies and regulations, etc., the power load uncertain and complex

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