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Technologies for a Sustainable Future: Towards Sustainable Energy Supply

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Energy Sustainability".

Deadline for manuscript submissions: 24 October 2025 | Viewed by 16589

Special Issue Editors


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Guest Editor
Department of Electrical and Electronic Engineering, University of Cagliari, Cagliari, Italy
Interests: circuits; static energy conversion; non destructive testing; artificial neural networks; magnetohydrodynamics
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Electrical and Electronic Engineering, University of Cagliari, Cagliari, Italy
Interests: mechanical design; biomedical instrumentation; material characterization; applied and computational mathematics; finite element modeling; solid waste management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Very often it is taken for granted that the objectives of developing and safeguarding the ecosystem give rise to an irremediable conflict. According to this view, humanity is faced with the choice between lowering their standard of living now or waiting for the consequences of their conduct to impose this choice in the future. Much of the debate is consumed on how far away this future is, implying that in many cases future generations are not considered as bearers of rights. At the heart of this debate is the supply and use of energy.

On the other hand, energy is the theme for which a third way is emerging, compared to the two previously indicated, which consists of adopting a smart approach. This is the combination of many components, primarily innovative technologies but also the analysis of consumption, the efficiency of transformation processes, the calculation of hidden costs and the examination of the entire life cycle of the devices that transform energy, thus including both the primary energy conversion systems as much as end users. This analysis is the basis for policies that aim to combine the well-being of humanity by avoiding conflict both among populations and between generations.

This Special Issue aims to collect the state of the art of technological, political, and economic solutions for the use of energy capable of favoring what is called "development of well-being", without setting geographical or time limits. Particular attention will be devoted to the production of electricity from renewable sources, but, in general, contributions are welcome that deal with processes that improve energy efficiency, which compare the real costs of conventional conversion processes with innovative ones, which analyze the economic and which define policies for the large-scale diffusion of smart solutions, and reports of successful actions in the implementation of smart solutions.

The objective of the Special Issue is to provide information from a technological, economic, and social policy point of view useful for undertaking actions capable of promoting sustainable use of energy.

We look forward to receiving your contributions.

Dr. Augusto Montisci
Dr. Aiman Rashid
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. Sustainability 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 2400 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

  • renewables, distributed generation
  • direct conversion of energy
  • smart grids
  • social policies for sustainability
  • hidden costs of energy

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Published Papers (9 papers)

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Research

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25 pages, 1583 KiB  
Article
Predicting China’s Provincial Carbon Peak: An Integrated Approach Using Extended STIRPAT and GA-BiLSTM Models
by Lian Chen, Hailan Chen and Yao Guo
Sustainability 2025, 17(15), 6819; https://doi.org/10.3390/su17156819 (registering DOI) - 27 Jul 2025
Abstract
As China commits to reaching peak carbon emissions and achieving carbon neutrality, accurately predicting the provincial carbon peak year is vital for designing effective, region-specific policies. This study proposes an integrated approach based on extended STIRPAT and GA-BiLSTM models to predict China’s provincial [...] Read more.
As China commits to reaching peak carbon emissions and achieving carbon neutrality, accurately predicting the provincial carbon peak year is vital for designing effective, region-specific policies. This study proposes an integrated approach based on extended STIRPAT and GA-BiLSTM models to predict China’s provincial carbon peak year. First, based on panel data across 30 provinces in China from 2000 to 2023, we construct a multidimensional indicator system that encompasses socioeconomic factors, energy consumption dynamics, and technological innovation using the extended STIRPAT model, which explains 87.42% of the variation in carbon emissions. Second, to improve prediction accuracy, a hybrid model combining GA-optimized BiLSTM networks is proposed, capturing temporal dynamics and optimizing parameters to address issues like overfitting. The GA-BiLSTM model achieves an R2 of 0.9415, significantly outperforming benchmark models with lower error metrics. Third, based on the model constructed above, the peak years are projected for baseline, low-carbon, and high-carbon scenarios. In the low-carbon scenario, 19 provinces are projected to peak before 2030, which is 8 more than in the baseline scenario. Meanwhile, under the high-carbon scenario, some provinces such as Jiangsu and Hebei may fail to peak by 2040. Finally, based on the predicted carbon peak year, provinces are categorized into four pathways—early, recent, later, and non-peaking—to provide targeted policy recommendations. This integrated framework significantly enhances prediction precision and captures regional disparities, enabling tailored decarbonization strategies that support China’s dual carbon goals of balancing economic growth with environmental protection. The approach provides critical insights for region-specific low-carbon transitions and advances sustainable climate policy modeling. Full article
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32 pages, 9140 KiB  
Article
The Synergistic Evolution and Coordination of the Water–Energy–Food Nexus in Northeast China: An Integrated Multi-Method Assessment
by Huanyu Chang, Yongqiang Cao, Jiaqi Yao, He Ren, Zhen Hong and Naren Fang
Sustainability 2025, 17(15), 6745; https://doi.org/10.3390/su17156745 - 24 Jul 2025
Viewed by 126
Abstract
The interconnections among water, energy, and food (WEF) systems are growing increasingly complex, making it essential to understand their evolutionary mechanisms and coordination barriers to enhance regional resilience and sustainability. In this study, we investigated the WEF system in Northeast China by constructing [...] Read more.
The interconnections among water, energy, and food (WEF) systems are growing increasingly complex, making it essential to understand their evolutionary mechanisms and coordination barriers to enhance regional resilience and sustainability. In this study, we investigated the WEF system in Northeast China by constructing a comprehensive indicator system encompassing resource endowment and utilization efficiency. The coupling coordination degree (CCD) of the WEF system was quantitatively assessed from 2001 to 2022. An obstacle degree model was employed to identify key constraints, while grey relational analysis was used to evaluate the driving influence of individual indicators. Furthermore, a co-evolution model based on logistic growth and competition–cooperation dynamics was developed to simulate system interactions. The results reveal the following: (1) the regional WEF-CCD increased from 0.627 in 2001 to 0.769 in 2022, reaching the intermediate coordination level, with the CCDs of the food, water, and energy subsystems rising from 0.39 to 0.62, 0.38 to 0.60, and 0.40 to 0.55, respectively, highlighting that the food subsystem had the most stable and significant improvement; (2) Jilin Province attained the highest WEF-CCD, 0.850, in 2022, while that for Heilongjiang remained the lowest, at 0.715, indicating substantial interprovincial disparities; (3) key indicators, such as food self-sufficiency rate, electricity generation, and ecological water use, functioned as both core constraints and major drivers of system performance; (4) co-evolution modeling revealed that the food subsystem exhibited the fastest growth, followed by water and energy (α3  > α1 >  α2 > 0), with mutual promotion between water and energy subsystems and inhibitory effects from the food subsystem, ultimately converging toward a stable equilibrium state; and (5) interprovincial co-evolution modeling indicated that Jilin leads in WEF system development, followed by Liaoning and Heilongjiang, with predominantly cooperative interactions among provinces driving convergence toward a stable and coordinated equilibrium despite structural asymmetries. This study proposes a transferable, multi-method analytical framework for evaluating WEF coordination, offering practical insights into bottlenecks, key drivers, and co-evolutionary dynamics for sustainable resource governance. Full article
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34 pages, 1525 KiB  
Article
Using Machine Learning to Model the Acceptance of Domestic Low-Carbon Technologies
by Paul van Schaik, Heather Clements, Yordanka Karayaneva, Elena Imani, Michael Knowles, Natasha Vall and Matthew Cotton
Sustainability 2025, 17(15), 6668; https://doi.org/10.3390/su17156668 - 22 Jul 2025
Viewed by 268
Abstract
This research addresses two specific knowledge gaps. The first regards the influence of domestic low-carbon technology (LCT) installation approaches and occupier status on user acceptance. The second is to demonstrate the role of machine learning techniques in producing an enhanced model-based understanding of [...] Read more.
This research addresses two specific knowledge gaps. The first regards the influence of domestic low-carbon technology (LCT) installation approaches and occupier status on user acceptance. The second is to demonstrate the role of machine learning techniques in producing an enhanced model-based understanding of domestic LCT acceptance. Together, these two approaches provide new insights into LCT acceptance through the theory of planned behaviour and demonstrate the value of machine learning for modelling such acceptance. Our aim is therefore to contribute to model-based knowledge about the acceptance of domestic LCTs. Specifically, we contribute new knowledge of the acceptance of LCTs according to the theory of planned behaviour and of the value of machine-learning techniques for modelling this acceptance. Through empirical research using an online quasi-experiment with 3813 English residents, we developed a model of low-carbon technology adoption and evaluated machine learning for model analysis. The design factors were the installation approach and occupier status, with main outcomes including adoption intention, willingness to accept, willingness to pay, attitude, subjective norm, and perceived behavioural control. To examine residents’ technology acceptance, we created two virtual reality models of technology implementation, differing in installation approach. For machine learning analysis, we employed nine techniques for model validation and predictor selection: linear regression, LASSO regression, ridge regression, support vector regression, regression tree (decision tree regression), random forest, XGBoost, k-NN, and neural network. LASSO regression emerged as the best technique in terms of predictor selection, with (near-)optimal model fit (R2 and MSE). We found that attitude, subjective norm, and perceived behavioural control significantly predicted the intention to adopt low-carbon technologies. The installation approach influenced willingness to accept, with higher intention for new-build installations than retrofits. Homeownership positively predicted perceived behavioural control, while age negatively predicted several outcomes. This study concludes with implications for policy and future research, a specific emphasis upon contemporary UK policy towards Future Homes Standards, and public information campaigns targeted to specific demographic user groups. This research demonstrates the value of an extended theory of planned behaviour model to study the acceptance of LCTs and the value of machine learning analysis in acceptance modelling. Full article
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17 pages, 5218 KiB  
Article
Exploring Extreme Voltage Events in Hydrogen Arcs within Electric Arc Furnaces
by Mohamad Al Nasser, Nashmi Alrasheedi, Ebrahim Karimi-Sibaki, Alexander Vakhrushev, Mahmoud Ahmadein, Sabbah Ataya and Abdellah Kharicha
Sustainability 2024, 16(7), 2831; https://doi.org/10.3390/su16072831 - 28 Mar 2024
Cited by 1 | Viewed by 1740
Abstract
This study highlights the potential utilization of hydrogen gas in electric arc furnaces for achieving cleaner and more sustainable steel production. The application of hydrogen offers a promising path for reducing carbon emissions, enhancing energy efficiency, and advancing the concept of “green steel”. [...] Read more.
This study highlights the potential utilization of hydrogen gas in electric arc furnaces for achieving cleaner and more sustainable steel production. The application of hydrogen offers a promising path for reducing carbon emissions, enhancing energy efficiency, and advancing the concept of “green steel”. This study employs a 2D axisymmetric induction-based model to simulate an electric arc under atmospheric pressure conditions. We conducted numerical simulations to compare compressible and incompressible models of an electric arc. The impact of compressibility on hydrogen arc characteristics such as arc velocity, temperature distribution, and voltage drop were investigated. Additionally, different applied current arcs were simulated using the compressible model. When compared to an incompressible arc, the compressible arc exhibits a higher voltage drop. This higher voltage drop is associated with lower temperatures and lower arc velocity. A rise in applied current results in an upward trend in the voltage drop and an increase in the arc radius. In addition, the increased applied current increases the probability of voltage fluctuations. The voltage fluctuations tend to become more extreme and exert more stress on the control circuit. This has an impact on emerging electric arc technologies, particularly those involving the use of hydrogen. These fluctuations affect arc stability, heat output, and the overall quality of processes. Thus, the precise prediction of voltage and the ability to stabilize the operation is critical for the successful implementation of new hydrogen technologies. Full article
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28 pages, 5881 KiB  
Article
Achieving Net Zero Condominiums through Energy Community Sharing
by Riccardo Trevisan, Mara Ladu, Emilio Ghiani and Ginevra Balletto
Sustainability 2024, 16(5), 2076; https://doi.org/10.3390/su16052076 - 1 Mar 2024
Cited by 4 | Viewed by 1672
Abstract
The European energy transition process is geared toward improving the economic viability of the energy sector through its democratization, which includes enabling citizens to generate, share, and sell energy produced by renewable sources. The current directives have led to the creation of energy [...] Read more.
The European energy transition process is geared toward improving the economic viability of the energy sector through its democratization, which includes enabling citizens to generate, share, and sell energy produced by renewable sources. The current directives have led to the creation of energy communities and collective self-consumption groups to engage and raise awareness among citizens, with the goal of achieving social, economic, and environmental benefits through shared renewable energy generation and consumption. In the near future, more and more of these initiatives are anticipated; therefore, innovative technological tools are necessary to assist their growth path. This research introduces a multi-criteria techno-economic simulation framework that enables the evaluation of several investment scenarios for various plant sizes and energy prices. The findings are useful during the investment planning phase as they help guide decision-making toward the objectives of economic, energy, and environmental sustainability. To evaluate the methodology, a case study of a collective self-consumption group located in a smart building in Italy is proposed. The results are discussed from statistical, technical, economic, and financial standpoints, demonstrating how the proposed approach can contribute to the development of collective self-consumption groups, risk hedging, and the goal of developing energy self-sufficiency based on the net-zero energy building concept. Full article
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13 pages, 6627 KiB  
Article
Carbon Nanotube Composites with Bimetallic Transition Metal Selenides as Efficient Electrocatalysts for Oxygen Evolution Reaction
by Shamas Riaz, Muhammad Shafiq Anjum, Abid Ali, Yasir Mehmood, Muhammad Ahmad, Norah Alwadai, Munawar Iqbal, Salih Akyürekli, Noor Hassan and Rizwan Shoukat
Sustainability 2024, 16(5), 1953; https://doi.org/10.3390/su16051953 - 27 Feb 2024
Cited by 5 | Viewed by 2237
Abstract
Hydrogen fuel is a clean and versatile energy carrier that can be used for various applications, including transportation, power generation, and industrial processes. Electrocatalytic water splitting could be the most beneficial and facile approach for producing hydrogen. In this work, transition metal selenide [...] Read more.
Hydrogen fuel is a clean and versatile energy carrier that can be used for various applications, including transportation, power generation, and industrial processes. Electrocatalytic water splitting could be the most beneficial and facile approach for producing hydrogen. In this work, transition metal selenide composites with carbon nanotubes (CNTs) have been investigated for electrocatalytic water splitting. The synthesis process involved the facile one-step hydrothermal growth of transition metal nanoparticles over the CNTs and acted as an efficient electrode toward electrochemical water splitting. Scanning electron microscopy and XRD patterns reveal that nanoparticles were firmly anchored on the CNTs, resulting in the formation of composites. The electrochemical measurements reveal that CNT composite with nickel–cobalt selenides (NiCo-Se/CNTs@NF) display remarkable oxygen evolution reaction (OER) activity in basic media, which is an important part of hydrogen production. It demonstrates the lowest overpotential (η10mAcm−2) of 0.560 V vs. RHE, a reduced Tafel slope of 163 mV/dec, and lower charge transfer impedance for the OER process. The multi-metallic selenide composite with CNTs demonstrating unique nanostructure and synergistic effects offers a promising platform for enhancing electrocatalytic OER performance and opens up new avenues for efficient energy conversion and storage applications. Full article
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18 pages, 4460 KiB  
Article
A Liquid Metal Alternate MHD Disk Generator
by Antoine Alemany, Arturs Brekis and Augusto Montisci
Sustainability 2023, 15(16), 12619; https://doi.org/10.3390/su151612619 - 21 Aug 2023
Cited by 2 | Viewed by 2403
Abstract
In this paper, an electrical generator is presented for the exploitation of alternating energy. Some renewable sources are directly available in such forms, such as the wave power obtainable from the sea, but most of them can be converted to alternative forms; therefore, [...] Read more.
In this paper, an electrical generator is presented for the exploitation of alternating energy. Some renewable sources are directly available in such forms, such as the wave power obtainable from the sea, but most of them can be converted to alternative forms; therefore, the proposed generator can be applied to different kinds of renewable sources. In particular, the proposed system is thought to be coupled with a thermoacoustic engine, which converts heat into mechanical vibration without using solid moving parts. This opens the proposed system to the use of most thermal sources, such as solar radiation, waste recovery, geothermic, car exhaust, and others. The object of of this present work concerns the transformation of alternating mechanical energy into electricity by using a specific type of magnetohydrodynamic (MHD) disk generator. The functioning of this generator is based on the interaction between a DC magnetic field embedded in a disk structure and a conducting fluid held in an inner channel. A simplified model of the generator is presented here, and a sensitivity analysis is performed. It is shown that, under specific operating conditions, the efficiency of the system can reach 70% with a level of power of hundreds of watts. Full article
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17 pages, 1945 KiB  
Article
Optimal Design of an Inductive MHD Electric Generator
by Sara Carcangiu, Alessandra Fanni and Augusto Montisci
Sustainability 2022, 14(24), 16457; https://doi.org/10.3390/su142416457 - 8 Dec 2022
Cited by 4 | Viewed by 3124
Abstract
In this paper, the problem of optimizing the design of an inductive Magneto-Hydro-Dynamic (MHD) electric generator is formalized as a multi-objective optimization problem where the conflicting objectives consist of maximizing the output power while minimizing the hydraulic losses and the mass of the [...] Read more.
In this paper, the problem of optimizing the design of an inductive Magneto-Hydro-Dynamic (MHD) electric generator is formalized as a multi-objective optimization problem where the conflicting objectives consist of maximizing the output power while minimizing the hydraulic losses and the mass of the apparatus. In the proposal, the working fluid is ionized with periodical pulsed discharges and the resulting neutral plasma is unbalanced by means of an intense DC electrical field. The gas is thus split into two charged streams, which induce an electromotive force into a magnetically coupled coil. The resulting generator layout does not require the use of superconducting coils and allows you to manage the issues related to the conductivity of the gas and the corrosion of the electrodes, which are typical limits of the MHD generators. A tailored multi-objective optimization algorithm, based on the Tabu Search meta-heuristics, has been implemented, which returns a set of Pareto optimal solutions from which it is possible to choose the optimal solution according to further applicative or performance constraints. Full article
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Review

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21 pages, 2927 KiB  
Review
MHD Generation for Sustainable Development, from Thermal to Wave Energy Conversion: Review
by José Carlos Domínguez-Lozoya, David Roberto Domínguez-Lozoya, Sergio Cuevas and Raúl Alejandro Ávalos-Zúñiga
Sustainability 2024, 16(22), 10041; https://doi.org/10.3390/su162210041 - 18 Nov 2024
Cited by 4 | Viewed by 3514
Abstract
Magnetohydrodynamic (MHD) generators are direct energy conversion devices that transform the motion of an electrically conducting fluid into electricity through interaction with a magnetic field. Developed as an alternative to conventional turbine-generator systems, MHD generators evolved through the 20th century from large units, [...] Read more.
Magnetohydrodynamic (MHD) generators are direct energy conversion devices that transform the motion of an electrically conducting fluid into electricity through interaction with a magnetic field. Developed as an alternative to conventional turbine-generator systems, MHD generators evolved through the 20th century from large units, which are intended to transform thermal energy into electricity using plasma as a working fluid, to smaller units that can harness heat from a variety of sources. In the last few decades, an effort has been made to develop energy conversion systems that incorporate MHD generators to harvest renewable sources such as solar and ocean energy, strengthening the sustainability of this technology. This review briefly synthesizes the main steps in the evolution of MHD technology for electricity generation, starting by outlining its physical principles and the proposals to convert thermal energy into electricity, either using a high-temperature plasma as a working fluid or a liquid metal in a one- or two-phase flow at lower temperatures. The use of wave energy in the form of acoustic waves, which were obtained from the conversion of thermal energy through thermoacoustic devices coupled to liquid metal and plasma MHD generators, as well as alternatives for the transformation of environmental energy resources employing MHD transducers, is also assessed. Finally, proposals for the conversion of ocean energy, mainly in the form of waves and tides, into electric energy, through MHD generators using either seawater or liquid metal as working fluids, are presented along with some of the challenges of MHD conversion technology. Full article
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