Industrial Energy Management System: Design of a Conceptual Framework using IoT and Big Data

Abstract

Industrial activities consume a large portion of the total energy demand worldwide, and thus, significantly contribute to greenhouse gas emissions. Hence, they face significant economic, social and environmental pressures to create energy efficient processes and systems of production and directly manage their energy consumption, looking at aspects beyond direct costs. One of the most effective ways to reduce energy consumption in the industrial sector is to implement an energy management system. Current research into Industrial Energy Management System (IEnMS) remains insufficient, and to the best of our knowledge, a holistic framework for an IEnMS using the IoT and big data does not exist. This paper provides a comprehensive systematic literature review of the existing academic publications on IEnMS. Further, the main requirements and components of an IEnMS are identified using literature. Based on these identified requirements and components, we have designed a theoretical framework for the IEnMS using IoT and big data analytics, forming a cyber-physical system. These results illustrate how the proposed framework provides an objective methodology that can be used to select the most suitable IEnMS for different industries based on their particular requirements.