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Enhancing Energy Efficiency in Industry 4.0 for Sustainable Production, Smart Design and Manufacturing, Demand-Side Management, and Efficient Scheduling with Renewable Energy Sources

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "B: Energy and Environment".

Deadline for manuscript submissions: closed (4 December 2024) | Viewed by 11467

Special Issue Editors

Dr. Raoudha Gaha

E-Mail Website
Guest Editor
Roberval Laboratory of Mechanics Royallieu Research Center, University of Technology of Compiègne, 60203 Compiègne CEDEX, France
Interests: eco-design; suatainable manufacturing; Industry 4.0 technologies
Dr. Berk Celik

E-Mail Website
Guest Editor
Avenues, Centre Pierre Guillaumat, Université de Technologie de Compiègne, 60203 Compiègne, France
Interests: power system; renewable energy; energy storage; demand response
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the current era of a global transition towards sustainability, the exploration of energy-saving and emission reduction strategies within industries and manufacturing processes has emerged as a significant international research focal point. This heightened focus stems from the recognition of the pivotal role played by industries in contributing to environmental challenges, and the urgent need to mitigate these impacts. In the green transition, energy-saving and emission reduction strategies in industries and manufacturing processes present an international research hotspot. Researchers are currently focused on the establishment of energy saving interventions via the development of measurement models, key performance indicators (KPI), smart technologies, sustainable design and manufacturing approaches, energy-efficient scheduling models, management procedures, or the search for renewable energy sources. In addition, emission reduction presents a relevant field of research in countries across the world because vigorously reducing the carbon emissions produced by industry will result in enormous, revolutionary changes. In essence, the dynamic interplay between energy-saving and emission reduction strategies within the manufacturing industry represents a multifaceted and globally relevant research pursuit. The outcomes of these endeavors hold the promise of not only mitigating the environmental impact of industrial processes, but also steering the industrial landscape toward a more sustainable and eco-friendly future. 

In detail, this upcoming Special Issue aims to serve as a guiding resource and help industrial entities to achieve heightened energy efficiency, diminish their carbon emissions, and advance overall sustainability through the incorporation of Industry 4.0 (I4.0) technologies. The scope of this Special Issue, but is not restricted to, the following topics:

  • Analysis of the current situation of sustainable industrial processes and the use of Industry 4.0 technologies in the assessment, measurement, and management of energy-saving and emission reduction strategies.
  • New proposed technologies for smart sustainable design and production.
  • Assessment of the impacts of emerging technologies on sustainability. 
  • Integration of renewable energies and energy storage for enhanced energy self-sufficiency. 
  • Integration of energy-efficient scheduling models in intelligent production systems.
  • In-depth exploration of demand-side management and demand–response integration in the manufacturing industry. 

Dr. Raoudha Gaha
Dr. Berk Celik
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sustainable production
  • Industry 4.0
  • renewable energy sources
  • demand-side management
  • energy-efficient scheduling

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Published Papers (5 papers)

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Research

16 pages, 2400 KiB  
Article
From Aggregate Production Planning to Aggregate Energy Industrial Consumption Plans
by Michel Leseure
Energies 2024, 17(24), 6388; https://doi.org/10.3390/en17246388 - 19 Dec 2024
Viewed by 751
Abstract
The increasing use of renewable energy sources in national electricity networks is challenging because of intermittence, i.e., the fact that the availability of the fuel (e.g., solar irradiance, wind) is volatile. This is a new challenge for the energy sector that has led [...] Read more.
The increasing use of renewable energy sources in national electricity networks is challenging because of intermittence, i.e., the fact that the availability of the fuel (e.g., solar irradiance, wind) is volatile. This is a new challenge for the energy sector that has led to much research about energy storage. In the manufacturing sector, dealing with the volatility of demand is not a new problem and is addressed by the application of aggregate production planning techniques. Solving an aggregate production planning problem is about finding the best trade-off because capacity and inventory utilization. This paper explores the application of this technique to energy management problems and explains how it can be used as a complementary solution to energy storage, showing how industrial entities can play an active role in greening the electricity sector, solely through a different planning of their inventory levels. Full article
(This article belongs to the Special Issue Enhancing Energy Efficiency in Industry 4.0 for Sustainable Production, Smart Design and Manufacturing, Demand-Side Management, and Efficient Scheduling with Renewable Energy Sources)
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23 pages, 2386 KiB  
Article
Sustainable Biomethanol and Biomethane Production via Anaerobic Digestion, Oxy-Fuel Gas Turbine and Amine Scrubbing CO2 Capture
by Towhid Gholizadeh, Hamed Ghiasirad and Anna Skorek-Osikowska
Energies 2024, 17(18), 4703; https://doi.org/10.3390/en17184703 - 21 Sep 2024
Cited by 1 | Viewed by 1813
Abstract
Energy policies around the world are increasingly highlighting the importance of hydrogen in the evolving energy landscape. In this regard, the use of hydrogen to produce biomethanol not only plays an essential role in the chemical industry but also holds great promise as [...] Read more.
Energy policies around the world are increasingly highlighting the importance of hydrogen in the evolving energy landscape. In this regard, the use of hydrogen to produce biomethanol not only plays an essential role in the chemical industry but also holds great promise as an alternative fuel for global shipping. This study evaluates a system for generating biomethanol and biomethane based on anaerobic digestion, biogas upgrading, methanol synthesis unit, and high-temperature electrolysis. Thermal integration is implemented to enhance efficiency by linking the oxy-fuel gas turbine unit. The integrated system performance is evaluated through thermodynamic modeling, and Aspen Plus V12.1 is employed for the analysis. Our findings show that the primary power consumers are the Solid Oxide Electrolysis Cell (SOEC) and Methanol Synthesis Unit (MSU), with the SOEC system consuming 824 kW of power and the MSU consuming 129.5 kW of power, corresponding to a production scale of 23.2 kg/h of hydrogen and 269.54 kg/h of biomethanol, respectively. The overall energy efficiency is calculated at 58.09%, considering a production output of 188 kg/h of biomethane and 269 kg/h of biomethanol. The amount of carbon dioxide emitted per biofuel production is equal to 0.017, and the proposed system can be considered a low-carbon emission system. Key findings include significant enhancements in biomethanol capacity and energy efficiency with higher temperatures in the methanol reactor. Full article
(This article belongs to the Special Issue Enhancing Energy Efficiency in Industry 4.0 for Sustainable Production, Smart Design and Manufacturing, Demand-Side Management, and Efficient Scheduling with Renewable Energy Sources)
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20 pages, 3316 KiB  
Article
Life Cycle Assessment of Piezoelectric Devices Implemented in Wind Turbine Condition Monitoring Systems
by Rabie Aloui, Raoudha Gaha, Barbara Lafarge, Berk Celik and Caroline Verdari
Energies 2024, 17(16), 3928; https://doi.org/10.3390/en17163928 - 8 Aug 2024
Cited by 2 | Viewed by 4280
Abstract
Assessing the vibration signature produced by a rotating component of the wind turbine enables the identification of operational conditions and the detection of potential faults at an early stage. The main purpose is to enhance the sustainability of wind turbines while increasing the [...] Read more.
Assessing the vibration signature produced by a rotating component of the wind turbine enables the identification of operational conditions and the detection of potential faults at an early stage. The main purpose is to enhance the sustainability of wind turbines while increasing the lifespan and uptime of their operational systems. This vibration analysis is based on the processing of the signal provided by sensors, which often incorporates piezoelectric transducers. This paper evaluates the consequences of employing piezoelectric sensors used for vibration measurement on electrical machines integrated into wind turbines by conducting a life cycle assessment (LCA). The widespread use of piezoelectric materials is due to their high sensitivity to vibrations, although their selection is also influenced by regulatory restrictions. This research focuses on the environmental impact of piezoelectric accelerometers used commonly in condition monitoring systems. The collected literature data on the manufacturing processes are inputted into the LCA model which is powered by the Ecoinvent 3 database. The impact assessment is carried out using the European ILCD 2011 Midpoint+ method by calculating the unique scores of the selected impact categories. The results are presented and discussed in terms of environmental indicators, as well as ecological recommendations on the design. Full article
(This article belongs to the Special Issue Enhancing Energy Efficiency in Industry 4.0 for Sustainable Production, Smart Design and Manufacturing, Demand-Side Management, and Efficient Scheduling with Renewable Energy Sources)
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24 pages, 6785 KiB  
Article
Hybrid PVP/Battery/Fuel Cell Wireless Charging Stations Using High-Frequency Optimized Inverter Technology for Electric Vehicles
by Gaith Baccouche, Mohamed Haikel Chehab, Chokri Ben Salah, Mehdi Tlija and Abdelhamid Rabhi
Energies 2024, 17(14), 3470; https://doi.org/10.3390/en17143470 - 15 Jul 2024
Cited by 2 | Viewed by 1980
Abstract
The design and integration of intelligent energy management systems in hybrid electric vehicle (EV) charging stations, leveraging industry 4.0 and renewable energy sources, is crucial for advancing sustainability, efficiency, and technological development. The innovative hybrid EV charging station described in this study uses [...] Read more.
The design and integration of intelligent energy management systems in hybrid electric vehicle (EV) charging stations, leveraging industry 4.0 and renewable energy sources, is crucial for advancing sustainability, efficiency, and technological development. The innovative hybrid EV charging station described in this study uses a combination of fuel cells, batteries, and solar panels that run at 14 amps a piece at 240 volts. The system consists of five essential components that work together to transfer power wirelessly: an EV battery bank, a boost converter, an HF inverter, transfer coils, and a power supply. Two crucial phases make up the optimization process. In phase 1, the boost converter’s maximum power point is tracked and optimized to generate the most power possible by varying the duty cycle between 10% and 90%. In phase 2, the HF uses a class ϕ2 inverter at 30 MHz to synchronize with the resonant frequency of wireless power transfer coils. Zero-voltage switching is used by a digital signal processor card to carry out control for effective operations. By utilizing hybrid sources to optimize power transmission, this design improves the sustainability of EV charging options. Full article
(This article belongs to the Special Issue Enhancing Energy Efficiency in Industry 4.0 for Sustainable Production, Smart Design and Manufacturing, Demand-Side Management, and Efficient Scheduling with Renewable Energy Sources)
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19 pages, 2481 KiB  
Article
Tackling Uncertainty: Forecasting the Energy Consumption and Demand of an Electric Arc Furnace with Limited Knowledge on Process Parameters
by Vanessa Zawodnik, Florian Christian Schwaiger, Christoph Sorger and Thomas Kienberger
Energies 2024, 17(6), 1326; https://doi.org/10.3390/en17061326 - 10 Mar 2024
Cited by 3 | Viewed by 1751
Abstract
The iron and steel industry significantly contributes to global energy use and greenhouse gas emissions. The rising deployment of volatile renewables and the resultant need for flexibility, coupled with specific challenges in electric steelmaking (e.g., operation optimization, optimized power purchasing, effective grid capacity [...] Read more.
The iron and steel industry significantly contributes to global energy use and greenhouse gas emissions. The rising deployment of volatile renewables and the resultant need for flexibility, coupled with specific challenges in electric steelmaking (e.g., operation optimization, optimized power purchasing, effective grid capacity monitoring), require accurate energy consumption and demand forecasts for electric steel mills to align with the energy transition. This study investigates diverse approaches to forecast the energy consumption and demand of an electric arc furnace—one of the largest consumers on the grid—considering various forecast horizons and objectives with limited knowledge on process parameters. The results are evaluated for accuracy, robustness, and costs. Two grid connection capacity monitoring approaches—a one-step and a multi-step Long Short-Term Memory neural network—are assessed for intra-hour energy demand forecasts. The one-step approach effectively models energy demand, while the multi-step approach encounters challenges in representing different operational phases of the furnace. By employing a combined statistic–stochastic model integrating a Seasonal Auto-Regressive Moving Average model and Markov chains, the study extends the forecast horizon for optimized day-ahead electricity procurement. However, the accuracy decreases as the forecast horizon lengthens. Nevertheless, the day-ahead forecast provides substantial benefits, including reduced energy balancing needs and potential cost savings. Full article
(This article belongs to the Special Issue Enhancing Energy Efficiency in Industry 4.0 for Sustainable Production, Smart Design and Manufacturing, Demand-Side Management, and Efficient Scheduling with Renewable Energy Sources)
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