Smart energy management: Energy consumption metering, monitoring and prediction for mining industry

• Published in: 2020 IEEE 2nd International Conference on Electronics, Control, Optimization and Computer Science (ICECOCS) pp. 1 - 5
• Main Authors: Laayati, Oussama, Bouzi, Mostafa, Chebak, Ahmed
• Format: Conference Proceeding
• Language: English
• Published: IEEE 02-12-2020
• Subjects: Artificial intelligence; Buildings; Digitization; Energy consumption; Energy management systems; Industries; ISO Standards; machine learning; Mining industry; Predictive models; SCADA systems; Smart city; Smart grid; Support vector machines
• DOI: 10.1109/ICECOCS50124.2020.9314532

With the evolution of technology, and the well-known concept of industry 4.0 and digitization, the energy is and always be an important factor in every field, and must follow up with the digitization revolution, introducing energy 4.0 where the energy production, transmission and consumption must be monitored and controlled in a smart way. The energy consumption is an end user, electrical utilities, environment and smart grid enormous problematic, this paper discusses the impact of energy consumption on energy management system according to ISO 50001, and gives approaches on how to apply the functionalities of industry 4.0 to digitize the energy, using smart meters and SCADA systems for monitoring and supervising it. It also introduces machine learning applications for energy consumption based on databases using some prediction models. This paper gives a comparison of earlier prediction models of energy consumption and the application field associated. It proposes an architecture of smart energy consumption system from field metering, communication, SCADA monitoring, storing in database, to predicting and forecasting for different applications e.g. mining industry, smart building and a university campus and shows an approach of the importance of this smart system in smart grid, smart cities and industry 4.0.