Implementation of digitalization technologies for optimizing energy efficiency and thermal management in steam industrial processes

In recent decades, within the framework of the digital world, the control and management of industrial steam consumption and demand have become increasingly difficult. Specifically, in complex industrial processes where spaces and layouts are limited, the possibility of modifying facilities and equipment is significantly less. In addition, the economic cost of controlling consumption per production line or equipment often makes investments unfeasible. Therefore, global consumption is usually controlled in the most complex industrial processes without any subsequent partial demand monitoring. This paper focuses on the development, implementation, and evaluation of a steam control platform by consumers, avoiding the need to install a mass flow meter by equipment, line or installation. An ad-hoc algorithm is designed and assessed by combining information from the monitoring and management systems for optimal operation. Data gathered through combined information from different management systems are integrated into a proposed global management and monitoring platform. In addition, the application of the designed steam control algorithm is used as key information for business decision-making, cost estimation, and predictive maintenance control. A case study and the proposed platform were implemented in an actual chemical plant located in Spain from a multinational corporation. This case study can also be used as a reference model, providing a scalable and easily replicable solution for other factories with steam-consuming equipment. From the results, it is possible to achieve effective steam consumption monitoring for over 50 production units by integrating steam flow meters into the main supply-lines, in combination with other industrial management systems: ERP, MES, or DCS. Notably, this approach is carried out with an investment cost 25 times lower than traditional methods, providing high efficiency, suitability and cost-effectiveness. The results and discussion of the gathered data and the global platform are also included in the paper. The proposed methodology and algorithms are not only suitable for this chemical company case study, but also scalable for any type of factory/plant with steam consumption equipment or process. • Development, implementation and evaluation of a steam control platform by consumers. • An ad hoc algorithm is designed and assembled for optimal steam operation. • Business decision-making, costs and predictive maintenance control are included. • Proposed methodology and algorithm suitable for any steam consumption process. • A case study implemented in a chemical plant of a multinational corporation.

Authors

Institutions

Publication Details

Journal
Renewable and Sustainable Energy Reviews
Published
2025-04-28
DOI
https://doi.org/10.1016/j.rser.2025.115783
Citations
3
Primary Topic
Advanced Power Generation Technologies
Type
article
Field-Weighted Citation Impact
2.19
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Implementation of digitalization technologies for optimizing energy efficiency and thermal management in steam industrial processes

F.M. Martínez-García, JOSE SANCHEZ ROBLES, Mariano Alarcón García, Faustino Camejo León
3 citations
Renewable and Sustainable Energy Reviews
Advanced Power Generation Technologies
2.19
article

Implementation of digitalization technologies for optimizing energy efficiency and thermal management in steam industrial processes

F.M. Martínez-García, JOSE SANCHEZ ROBLES, Mariano Alarcón García, Faustino Camejo León
article en
3 citations

Abstract

In recent decades, within the framework of the digital world, the control and management of industrial steam consumption and demand have become increasingly difficult. Specifically, in complex industrial processes where spaces and layouts are limited, the possibility of modifying facilities and equipment is significantly less. In addition, the economic cost of controlling consumption per production line or equipment often makes investments unfeasible. Therefore, global consumption is usually controlled in the most complex industrial processes without any subsequent partial demand monitoring. This paper focuses on the development, implementation, and evaluation of a steam control platform by consumers, avoiding the need to install a mass flow meter by equipment, line or installation. An ad-hoc algorithm is designed and assessed by combining information from the monitoring and management systems for optimal operation. Data gathered through combined information from different management systems are integrated into a proposed global management and monitoring platform. In addition, the application of the designed steam control algorithm is used as key information for business decision-making, cost estimation, and predictive maintenance control. A case study and the proposed platform were implemented in an actual chemical plant located in Spain from a multinational corporation. This case study can also be used as a reference model, providing a scalable and easily replicable solution for other factories with steam-consuming equipment. From the results, it is possible to achieve effective steam consumption monitoring for over 50 production units by integrating steam flow meters into the main supply-lines, in combination with other industrial management systems: ERP, MES, or DCS. Notably, this approach is carried out with an investment cost 25 times lower than traditional methods, providing high efficiency, suitability and cost-effectiveness. The results and discussion of the gathered data and the global platform are also included in the paper. The proposed methodology and algorithms are not only suitable for this chemical company case study, but also scalable for any type of factory/plant with steam consumption equipment or process. • Development, implementation and evaluation of a steam control platform by consumers. • An ad hoc algorithm is designed and assembled for optimal steam operation. • Business decision-making, costs and predictive maintenance control are included. • Proposed methodology and algorithm suitable for any steam consumption process. • A case study implemented in a chemical plant of a multinational corporation.

Renewable and Sustainable Energy ReviewsVol. 217
Universidad Politécnica de Cartagena (ES), Takasago (United States) (US), Universidad de Murcia (ES)
Affordable and clean energy
Openalex Percentile: Top 13%
Advanced Power Generation Technologies
2.19
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.