A Situational Awareness Model of Regional Power Demand Based on Stacking Technology

Abstract

The effective application of electric power big data can better reflect the influencing factors of electricity demand and its inherent laws. This paper introduces big data and its related technology to the study of electricity demand. By selecting variables from five aspects such as historical electricity consumption by industry, weather, economy, industry attributes, and holidays, stacking fusion technology is used to construct a regional electricity demand situational awareness model to predict industry and regional electricity consumption trends. The empirical evaluations demonstrate that the integration model possesses notable capacity for combining diverse factors, thereby enhancing the precision of electricity consumption forecasts.