Context-Based Decision Support System for Energy Efficiency in Industrial Plants

Abstract

Industrial companies must actively pursue more energy efficiency in their processes, with impacts on both costs and the environment, and ultimately business performance. This article explores the influence of context around the manufacturing process on energy consumption. By creating awareness of this influence in a quantified way, it is possible, via a structured decision process, to find opportunities and derive solutions to improve energy performance. This work introduces a method developed in the scope of the LifeSaver project, which is based on the visualization of energy consumption data against benchmark/average values. The overall approach is supported by a software platform which offers a set of functionalities covering the complete approach, from the detection of the consumption pattern to the implementation of improvement solutions. The approach was tested in two industrial business cases. The first one illustrates the approach by showing the influence of the human factor on the energy performance in cement production. The second case deals with finding opportunities on the selection of the operation point, and its impact on peak load management. The proposed approach and developed system demonstrate a positive direct impact on reducing energy consumption and consequent carbon dioxide emissions. Furthermore, the operation of the implemented case studies has an important indirect effect on bringing awareness to the impact of small actions on general energy efficiency.