Context-based Multi-Model Energy Prediction Algorithm Using RLS Estimation

The subject of this paper is developed in the scope of decision support to reduce energy consumption in industrial processes. It starts from the observation that context under production units are producing might have a strong influence on the specific energy consumption. In this line, this paper proposes an approach to model energy consumption taking the value of context variables in consideration. The approach is based on the estimation of multiple models, using RLS and valid in identified context regions, collecting the necessary knowledge to support future decision making processes. An example using experimental data from a cement factory is used to illustrate the proposed methodology.