A distribution transformer overload prediction method considering load growth rate and user power consumption characteristics

Abstract

The invention belongs to the technical field of electric power engineering, and specifically relates to a distribution transformer weight overload prediction method considering the load growth rate and the user's power consumption characteristics. and other data that affect the operation status of distribution transformers. Through these massive data, the K-means algorithm and the distribution transformer load prediction model based on deep belief network (DBN) are used to predict the load rate of each distribution transformer, so as to realize the Early warning of heavy and overloaded operating status of distribution transformers, improvement of operating status of distribution transformers and improvement of power supply quality in distribution network areas.

Description

technical field [0001] The invention belongs to the technical field of electric power engineering, and in particular relates to a distribution transformer weight overload prediction method considering load growth rate and user power consumption characteristics. Background technique [0002] The rapid development of economic construction has promoted the revolution of the electric power industry. At the same time, with the continuous improvement of people's quality of life, whether it is industrial electricity, commercial electricity or residential electricity, the electricity consumption is growing rapidly, and the growth trend is diversified. In different power consumption areas, the daily load curve is affected by factors such as seasons, weather conditions, characteristic days and power consumption areas, showing huge differences in different scenarios, and some loads have great peak-to-valley differences. Among them, the frequency of use of high-power electrical applianc...

AI Technical Summary

Problems solved by technology

Among them, the frequency of use of high-power electrical appliances has increased significantly, which will lead to a sharp increase in power consumption, causing the distribution transformer to operate to a critical capacity, in a bad operating state of heavy load or even overload, and even cause the transformer to burn out

Especially in the special period of major holidays such as summer with high temperature and Spring Festival, there is a high incidence of transformer faults, which leads to an increase in the complaint rate of residents and heavy economic losses

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