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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: 4 December 2024 | Viewed by 1652

Special Issue Editors


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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
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

Published Papers (2 papers)

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Research

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
Viewed by 491
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
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20 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
Viewed by 793
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
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Life cycle assessment of piezoelectric devices implemented inwind turbine condition monitoring systems
Authors: Rabie ALOUI; Raoudha GAHA; Barbara LAFARGE; Berk CELIK; Caroline VERDARI
Affiliation: Laboratoire Roberval, Université de Technologie de Compiègne
Abstract: Asset condition monitoring has become a major issue over the last decade, which concerns the development of sensing systems that transmit accurate and reliable data for predictive mainte- nance. Several techniques have emerged in the literature with the common purpose of monitoring the condition of operational equipment in service. Assessing the vibration signature produced by a rotating component of the wind turbine, and more particularly on electrical generators, enables the identification of operational conditions and the detection of potential faults at an early stage. The goal is to increase the lifetime and availability of wind turbine operational systems to make them more sustainable. This vibration analysis is based on the processing of the signal provided by sensors which often incorporates electromechanical transducers, such as piezoelectric, magnetostructive, or others. This paper aims to evaluate the consequences of employing piezoelectric sensors used for vibration measurement on electrical machines integrated into wind turbines by conducting a life cycle assessment. The high sensitivity of piezoelectric materials to vibrations is the reason for their widespread use. The choice of piezoelectric materials comes from a regulatory perspective which aims to restrict its use. This research focuses on the environmental impact of a piezoelectric accelerometers used commonly in condition monitoring systems. Several transducer devices are first presented with an emphasis on ecodesign and alternatives. The environmental assessment of these devices is then investigated from a macro perspective with 16 impact categories. Results are presented and discussed in terms of environmental indicators, as well as environmental recommendations on their designs.

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