Meteorological Factors Considered Load Decoupling Forecasting Techniques

Abstract

In this paper, a similar historical meteorological data search technique was put forward. This method took the weather forecasting data as clustering center, found those days that had the similarity weather factors, and then decoupled these loads into secular trend load and meteorological load as sample data for load forecasting. This method can improve the similarity of the loads between forecast day and sample days. Simulation results showed that these methods are valid and can make the load forecast more precision.