Hotspot Analysis of Short-term Load Forecasting Based on Knowledge Graph

摘要

Short-term load forecasting is instructive to the daily work of the electrical industry, and the analysis of its evolutionary trends and changes of hotspot will promote the development of this field. Based on 5,984 literatures in the field of short-term load forecasting from 2012 to 2020 in the WOS database, Citespace was used to generate keyword cooccurrence maps and co-cited maps, and in-depth analysis of hotspot in the field of power load prediction in the form of visual analysis. The results show that load forecasting technology is dominated by deep learning, and load forecasting is applied to user energy management.