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Selected Papers from the SDEWES 2024 Conference on Sustainable Development...
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Selected Papers from the SDEWES 2024 Conference on Sustainable Development of Energy, Water and Environment Systems

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

Deadline for manuscript submissions: closed (31 March 2025) | Viewed by 4712

Special Issue Editors

Prof. Dr. Francesco Calise

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Guest Editor
Department of Industrial Engineering, University of Naples Federico II, 80125 Naples, Italy
Interests: fuel cells; advanced optimization techniques; solar thermal systems; concentrating photovoltaic/thermal photovoltaic systems; energy saving in buildings; solar heating and cooling; organic Rankine cycles; geothermal energy; dynamic simulations of energy systems; renewable polygeneration systems
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Qiuwang Wang

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Guest Editor
Key Laboratory of Thermo-Fluid Science and Engineering, Ministry of Education, Xi’an Jiaotong University, Xi’an 710049, China
Interests: heat transfer enhancement and its applications to engineering problems; high-temperature heat transfer and fluid flow; transport phenomena in porous media; numerical simulation, prediction, and optimization
Special Issues, Collections and Topics in MDPI journals
Dr. Maria Vicidomini

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Guest Editor
Department of Industrial Engineering, University of Naples Federico II, 80125 Naples, Italy
Interests: solar systems; energy saving in buildings; solar desalination; dynamic simulations of energy systems; renewable polygeneration systems
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Wenxiao Chu

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Guest Editor
Key Laboratory of Thermo-Fluid Science and Engineering (Ministry of Education), Xi’an Jiaotong University, Xi’an 710049, China
Interests: energy systems; enhanced heat transfer; thermal management; heating, ventilating, and air conditioning (HVAC); supercritical fluid
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Poul Alberg Østergaard

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Guest Editor
Department of Planning, Aalborg University, 9000 Aalborg, Denmark
Interests: energy systems; energy scenarios; renewable energy system integration; energy and development; environmental impacts from energy development
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the last few decades, the integration and improvement in the energy efficiency of several sectors regarding electricity, heating, cooling, transport, water, buildings, waste, wastewater, industry, forestry and agriculture systems have become more and more pivotal. Considering the importance of a social system based on the sustainability concept and the efforts made to reduce greenhouse gas emissions, the SDEWES Conferences have become a significant platform for researchers in those areas to meet, discuss, share and disseminate new ideas.

In this framework, energy saving and emission reduction are pivotal to mitigating human environmental fingerprints. Even with significant attention devoted to the importance and merits of sustainable energy supply over the last few decades, there are still significant gaps to be filled with respect to how to design and implement technically optimal energy systems at the lowest costs.

This Special Issue aims to provide an important contribution by presenting the state of the art in sustainable energy supply solutions, ranging from the technical analyses of energy components on both the supply and demand sides to energy scenarios and pathways. This Special Issue particularly welcomes SDEWES papers that address energy systems without traditional sector boundaries between electricity, heating, cooling, transportation and industrial demands and that consider the integration and synergies between these sectors.

The 19th Conference on Sustainable Development of Energy, Water and Environment Systems—the SDEWES Conference—was held on 8-12 September in Rome (Italy). The 4th LA Conference on Sustainable Development of Energy, Water and Environment Systems (SDEWES) was held on 14–17 January 2024 in Vina del Mar, Chile. The 2nd AP Conference on Sustainable Development of Energy, Water and Environment Systems (SDEWES) was held on 02-05 April 2024 in the Gold Coast, Australia. These SDEWES Conferences are dedicated to the improvement and dissemination of knowledge on methods, policies and technologies for increasing the sustainability of n taking into account its economic, environmental and social pillars.

Prof. Dr. Francesco Calise
Prof. Dr. Qiuwang Wang
Dr. Maria Vicidomini
Prof. Dr. Wenxiao Chu
Prof. Dr. Poul Alberg Østergaard
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

  • waste to energy
  • biocircular economy
  • power-to-X
  • smart energy systems
  • energy policy
  • water–energy nexus
  • renewable energy resources for power and heat generation
  • district heating and/or cooling
  • advanced sustainable energy conversion and storage systems
  • biofuels and alternative fuels
  • hybrid and electric vehicles
  • cogeneration, trigeneration and polygeneration
  • electricity transmission and distribution
  • security of gas supply
  • energy efficiency in industry and buildings
  • energy markets

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Related Special Issues

Published Papers (6 papers)

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Research

25 pages, 10597 KiB  
Article
Optimizing Bifacial Solar Modules with Trackers: Advanced Temperature Prediction Through Symbolic Regression
by Fabian Alonso Lara-Vargas, Carlos Vargas-Salgado, Jesus Águila-León and Dácil Díaz-Bello
Energies 2025, 18(8), 2019; https://doi.org/10.3390/en18082019 - 15 Apr 2025
Viewed by 552
Abstract
Accurate temperature prediction in bifacial photovoltaic (PV) modules is critical for optimizing solar energy systems. Conventional models face challenges to balance accuracy, interpretability, and computational efficiency. This study addresses these limitations by introducing a symbolic regression (SR) framework based on genetic algorithms to [...] Read more.
Accurate temperature prediction in bifacial photovoltaic (PV) modules is critical for optimizing solar energy systems. Conventional models face challenges to balance accuracy, interpretability, and computational efficiency. This study addresses these limitations by introducing a symbolic regression (SR) framework based on genetic algorithms to model nonlinear relationships between environmental variables and module temperature without predefined structures. High-resolution data, including solar radiation, ambient temperature, wind speed, and PV module temperature, were collected at 5 min intervals over a year from a 19.9 MW bifacial PV plant with trackers in San Marcos, Colombia. The SR model performance was compared with multiple linear regression, normal operating cell temperature (NOCT), and empirical regression models. The SR model outperformed others by achieving a root mean squared error (RMSE) of 4.05 °C, coefficient of determination (R2) of 0.91, Spearman’s rank correlation coefficient of 0.95, and mean absolute error (MAE) of 2.25 °C. Its hybrid structure combines linear ambient temperature dependencies with nonlinear trigonometric terms capturing solar radiation dynamics. The SR model effectively balances accuracy and interpretability, providing information for modeling bifacial PV systems. Full article
(This article belongs to the Special Issue Selected Papers from the SDEWES 2024 Conference on Sustainable Development of Energy, Water and Environment Systems)
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22 pages, 1288 KiB  
Article
Short-Term Electric Load Forecasting for an Industrial Plant Using Machine Learning-Based Algorithms
by Oğuzhan Timur and Halil Yaşar Üstünel
Energies 2025, 18(5), 1144; https://doi.org/10.3390/en18051144 - 26 Feb 2025
Cited by 1 | Viewed by 822
Abstract
As the global energy landscape evolves towards sustainability, the extensive usage of fossil fuels in electricity generation is progressively diminishing, while the contribution of renewable energy sources is steadily increasing. In this evolving scenario, the importance of load forecasting cannot be overstated in [...] Read more.
As the global energy landscape evolves towards sustainability, the extensive usage of fossil fuels in electricity generation is progressively diminishing, while the contribution of renewable energy sources is steadily increasing. In this evolving scenario, the importance of load forecasting cannot be overstated in optimizing energy management and ensuring the efficient operation of industrial plants regardless of their scale. By accurately anticipating energy demand, industrial facilities can enhance efficiency, reduce costs, and facilitate the adoption of renewable energy technologies in the power grid. Recent studies have emphasized the pervasive utilization of machine learning-based algorithms in the field of electric load forecasting for industrial plants. Their capacity to analyze intricate patterns and enhance prediction accuracy renders them a favored option for enhancing energy management and operational efficiency. The present analysis revolves around the creation of short-term electric load forecasting models for a large industrial plant operating in Adana, Turkey. The integration of calendar, meteorological, and lagging electrical variables, along with machine learning-based algorithms, is employed to boost forecasting accuracy and optimize energy utilization. The ultimate objective of the present study is to conduct a thoroughgoing and detailed analysis of the statistical performance of the models and associated error metrics. The metrics employed include the R2 and MAPE values. Full article
(This article belongs to the Special Issue Selected Papers from the SDEWES 2024 Conference on Sustainable Development of Energy, Water and Environment Systems)
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32 pages, 23330 KiB  
Article
Study on the Combustion Behavior of Inhomogeneous Partially Premixed Mixtures in Confined Space
by Yanfei Li, Xin Zhang, Lichao Chen and Ying Liu
Energies 2025, 18(4), 899; https://doi.org/10.3390/en18040899 - 13 Feb 2025
Viewed by 417
Abstract
Reasonably configuring the concentration distribution of the mixture to achieve partially premixed combustion has been proven to be an effective method for improving energy utilization efficiency. However, due to the significant influence of concentration non-uniformity and flow field disturbances, the combustion behavior and [...] Read more.
Reasonably configuring the concentration distribution of the mixture to achieve partially premixed combustion has been proven to be an effective method for improving energy utilization efficiency. However, due to the significant influence of concentration non-uniformity and flow field disturbances, the combustion behavior and mechanisms of partially premixed combustion have not been fully understood or systematically analyzed. In this study, the partially premixed combustion characteristics of methane–hydrogen–air mixtures in a confined space were investigated, focusing on the combustion behavior and key parameter variation patterns under different equivalence ratios (0.5, 0.7, 0.9) and hydrogen contents (10%, 20%, 30%, 40%). The global equivalence ratio and degree of partial premixing of the mixture were controlled by adjusting the fuel injection pulse width and ignition timing, thereby regulating the concentration field and flow field distribution within the combustion chamber. The constant-pressure method was used to calculate the burning velocity. Results show that as the mixture formation time decreases, the degree of partial premixing increases, accelerating the heat release process, increasing burning velocity, and shortening the combustion duration. It exhibits rapid combustion characteristics, particularly during the initial combustion phase, where flame propagation speed and heat release rate increase significantly. The burning velocity demonstrates a distinct single-peak profile, with the peak burning velocity increasing and its occurrence advancing as the degree of partial premixing increases. Additionally, hydrogen’s preferential diffusion effect is enhanced with increasing mixture partial premixing, making the combustion process more efficient and concentrated. This effect is particularly pronounced under low-equivalence-ratio (lean burn) conditions, where the combustion reaction rate improves more significantly, leading to greater combustion stability. The peak of the partially premixed burning velocity occurs almost simultaneously with the peak of the second-order derivative of the combustion pressure. This phenomenon highlights the strong correlation between the combustion reaction rate and the dynamic variations in pressure. Full article
(This article belongs to the Special Issue Selected Papers from the SDEWES 2024 Conference on Sustainable Development of Energy, Water and Environment Systems)
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23 pages, 2708 KiB  
Article
Optimization of Biomass to Bio-Syntetic Natural Gas Production: Modeling and Assessment of the AIRE Project Plant Concept
by Emanuele Di Bisceglie, Alessandro Antonio Papa, Armando Vitale, Umberto Pasqual Laverdura, Andrea Di Carlo and Enrico Bocci
Energies 2025, 18(3), 753; https://doi.org/10.3390/en18030753 - 6 Feb 2025
Viewed by 570
Abstract
This study focuses on the modeling, simulation, and optimization of an integrated biomass gasification and methanation process to produce bio-synthetic natural gas (Bio-SNG) as part of the AIRE project. The process was simulated using Aspen Plus® software (V14), incorporating experimental results from [...] Read more.
This study focuses on the modeling, simulation, and optimization of an integrated biomass gasification and methanation process to produce bio-synthetic natural gas (Bio-SNG) as part of the AIRE project. The process was simulated using Aspen Plus® software (V14), incorporating experimental results from pilot-scale gasification setups. Key steps involved syngas production in a dual fluidized bed gasifier and its subsequent conversion to Bio-SNG in a methanation section. Heat integration strategies were implemented to enhance system results demonstrate that optimized heat recovery, achieved by utilizing exothermic methanation reactions to preheat gasification inputs, eliminates the need for auxiliary fuel in the gasification process. The optimized system achieved a thermal recovery rate of 80%, a cold gas efficiency of 79%, a Bio-SNG production rate of 0.4 Nm3/kgBiom, and a methane content of 85 vol.%. These optimizations reduced CO2 emissions by 10% while increasing overall energy efficiency. This work highlights the potential of integrating biomass gasification and methanation processes with heat recovery for sustainable methane production. The findings provide a basis for scaling up the process and further exploring syngas utilization pathways to produce renewable energy carriers. Full article
(This article belongs to the Special Issue Selected Papers from the SDEWES 2024 Conference on Sustainable Development of Energy, Water and Environment Systems)
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22 pages, 3404 KiB  
Article
Modelling and Transient Simulation of District Heating Networks Based on a Control Theory Approach
by Dominik Schojda, Jan Scheipers, Jürgen Roes and Harry Hoster
Energies 2025, 18(3), 658; https://doi.org/10.3390/en18030658 - 31 Jan 2025
Viewed by 719
Abstract
Heating districts have become one of the key infrastructures to efficiently and sustainably supply heat to consumers. With the current climate change crisis, not only are heating districts of the essence but their efficient and optimized operation as well. To analyze and achieve [...] Read more.
Heating districts have become one of the key infrastructures to efficiently and sustainably supply heat to consumers. With the current climate change crisis, not only are heating districts of the essence but their efficient and optimized operation as well. To analyze and achieve such an optimization, transient simulations of heating districts are needed. These simulations are a means of upgrading older town networks to smarter energy grids as well as an effective tool for the planning and building of newer heating networks. Therefore, this work presents an easy simulation method for the transient simulation of heating districts based on a control theory approach. The simulation method can calculate multiple-loop networks as well as non-looped networks and correctly predict how a heating network can behave over time. Additionally, this approach allows for the inclusion of new renewable energy sources into existing heating networks and to simulate the resulting network behavior. The method was tested on five different testcases involving a single-loop network, a multiple-loop network, and a real-life non-looped network. In each case, the calculated massflows were validated with the software Epanet (Version 2.2), while the simulated temperatures were compared to the theoretical steady-state values as well as the theoretical times of arrival of each heating network. The simulation results present a good approximation in each testcase. Finally, the limitations of the method are discussed, and a recommendation for the usage of the approach is given. Full article
(This article belongs to the Special Issue Selected Papers from the SDEWES 2024 Conference on Sustainable Development of Energy, Water and Environment Systems)
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33 pages, 7794 KiB  
Article
Effects on the Unit Commitment of a District Heating System Due to Seasonal Aquifer Thermal Energy Storage and Solar Thermal Integration
by Joana Verheyen, Christian Thommessen, Jürgen Roes and Harry Hoster
Energies 2025, 18(3), 645; https://doi.org/10.3390/en18030645 - 30 Jan 2025
Viewed by 782
Abstract
The ongoing transformation of district heating systems (DHSs) aims to reduce emissions and increase renewable energy sources. The objective of this work is to integrate solar thermal (ST) and seasonal aquifer thermal energy storage (ATES) in various scenarios applied to a large DHS. [...] Read more.
The ongoing transformation of district heating systems (DHSs) aims to reduce emissions and increase renewable energy sources. The objective of this work is to integrate solar thermal (ST) and seasonal aquifer thermal energy storage (ATES) in various scenarios applied to a large DHS. Mixed-integer linear programming (MILP) is used to develop a comprehensive model that minimizes operating costs, including heat pumps (HPs), combined heat and power (CHP) units, electric heat boilers (EHBs), heat-only boilers (HOBs), short-term thermal energy storage (TES), and ATES. Different ATES scenarios are compared to a reference without seasonal TES (potential of 15.3 GWh of ST). An ATES system with an injection well temperature of about 55 °C has an overall efficiency of 49.8% (58.6% with additional HPs) and increases the integrable amount of ST by 178% (42.5 GWh). For the scenario with an injection well temperature of 20 °C and HPs, the efficiency is 86.6% and ST is increased by 276% (57.5 GWh). The HOB heat supply is reduced by 8.9% up to 36.6%. However, the integration of an ATES is not always economically or environmentally beneficial. There is a high dependency on the configurations, prices, or emissions allocated to electricity procurement. Further research is of interest to investigate the sensitivity of the correlations and to apply a multi-objective MILP optimization. Full article
(This article belongs to the Special Issue Selected Papers from the SDEWES 2024 Conference on Sustainable Development of Energy, Water and Environment Systems)
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