Journal Description
Energies
Energies
is a peer-reviewed, open access journal of related scientific research, technology development, engineering policy, and management studies related to the general field of energy, from technologies of energy supply, conversion, dispatch, and final use to the physical and chemical processes behind such technologies. Energies is published semimonthly online by MDPI. The European Biomass Industry Association (EUBIA), Association of European Renewable Energy Research Centres (EUREC), Institute of Energy and Fuel Processing Technology (ITPE), International Society for Porous Media (InterPore), CYTED and others are affiliated with Energies and their members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), Ei Compendex, RePEc, Inspec, CAPlus / SciFinder, and other databases.
- Journal Rank: CiteScore - Q1 (Engineering (miscellaneous))
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.1 days after submission; acceptance to publication is undertaken in 3.3 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Sections: published in 41 topical sections.
- Testimonials: See what our editors and authors say about Energies.
- Companion journals for Energies include: Fuels, Gases, Nanoenergy Advances and Solar.
Impact Factor:
3.2 (2022);
5-Year Impact Factor:
3.3 (2022)
Latest Articles
Evaluation of Lost Circulation Material Sealing for Geothermal Drilling
Energies 2024, 17(11), 2703; https://doi.org/10.3390/en17112703 (registering DOI) - 2 Jun 2024
Abstract
Lost circulation is a pervasive problem in geothermal wells that can create prohibitive costs during drilling. The main issue with treatment is that the mechanism of plug formation is poorly understood. Here we applied two experimental approaches to characterize the clogging effectiveness of
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Lost circulation is a pervasive problem in geothermal wells that can create prohibitive costs during drilling. The main issue with treatment is that the mechanism of plug formation is poorly understood. Here we applied two experimental approaches to characterize the clogging effectiveness of different materials. Fracture flow tests with different geometries were conducted with various individual materials and mixtures at relevant conditions. A high-temperature flow loop system was also developed to inject single- and mixed-material plugs into a gravel pack with a non-uniform geometry to compare with the fracture tests. The fracture tests revealed that single materials tended to form no plug or an unstable plug, while mixtures of materials were uniformly better at sealing fractures. Gravel pack tests at high temperatures show most of the materials are intact but degraded. The fibrous materials can create partial or unstable plugs in the gravel pack, but mixed-material plugs are far more effective at clogging. Both test types suggest that (1) mixed materials are more effective at blocking fluid flow and (2) fibrous materials seal fracture openings better, while granular materials seal inside fractures or pore throats better. Further research is needed to study the long-term stability of different plug configurations.
Full article
(This article belongs to the Special Issue Leading the Way in Hydraulic Fracturing and Reservoir Technologies)
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Open AccessArticle
Multi-Aspect Shaping of the Building’s Heat Balance
by
Aleksander Starakiewicz, Przemysław Miąsik, Joanna Krasoń and Bożena Babiarz
Energies 2024, 17(11), 2702; https://doi.org/10.3390/en17112702 (registering DOI) - 2 Jun 2024
Abstract
In the European Union, buildings account for 42% of the energy consumption and 36% of the direct and indirect energy-related greenhouse gas emissions. Reducing thermal power for heating purposes is crucial to achieve climate neutrality. The main purpose of this article is to
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In the European Union, buildings account for 42% of the energy consumption and 36% of the direct and indirect energy-related greenhouse gas emissions. Reducing thermal power for heating purposes is crucial to achieve climate neutrality. The main purpose of this article is to identify the places in the building where it is possible to significantly improve energy efficiency through the use of appropriate construction and material solutions. This article contains a multi-aspect approach to the heat balance of a building. Solutions that have a direct impact on building energy consumption were analysed, taking into account architectural, technological, and material aspects. Particular attention was paid to energy-efficient design and material solutions for non-transparent and transparent external walls and thermal storage walls (Trombe walls). An analysis of heat transfer through building elements was carried out, along with the optimisation of energy-efficient solutions for non-transparent and transparent barriers. Two methods for determining the equivalent heat transfer coefficient Ue for solar active partitions are presented. The analysis presented in the work using the original method of the balanced heat transfer coefficient Ue is a testing ground for identifying unfavourable features of the building structure, as well as the most energy-efficient solutions that can be used in establishing standards for the construction and modernisation of buildings. The value of the Ue coefficient illustrates the actual heat transfer through the partition. Having Ue values for various structural solutions of building envelopes, the designer can easily select the most effective ones. The use of the presented methodology will allow for the optimisation of technical solutions for building elements to improve its energy efficiency.
Full article
(This article belongs to the Special Issue Recent Developments in Heat Transfer: Towards Climate Neutrality)
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Open AccessArticle
Second-Order Sliding-Mode Control Applied to Microgrids: DC & AC Buck Converters Powering Constant Power Loads
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Miguel Monsalve-Rueda, John E. Candelo-Becerra and Fredy E. Hoyos
Energies 2024, 17(11), 2701; https://doi.org/10.3390/en17112701 (registering DOI) - 2 Jun 2024
Abstract
Microgrids are designed to connect different types of AC and DC loads, which require robust power controllers to achieve an efficient power transfer. However, the effects of both AC and DC disturbances in the same type of controller make achieving stability a design
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Microgrids are designed to connect different types of AC and DC loads, which require robust power controllers to achieve an efficient power transfer. However, the effects of both AC and DC disturbances in the same type of controller make achieving stability a design challenge, especially in coupled systems where disturbances affect both the upstream and downstream in the microgrid. This paper presents an analysis of a second-order sliding-mode control (SOSMC) applied to a microgrid with direct-current (DC) and alternating-current (AC) power converters. The aim is to simulate the second-order sliding-mode control with buck converters that feed constant DC–DC and DC–AC power loads. The controller was tested in consideration of a unique sliding surface facing external disturbances, such as variations in the frequency of AC converters, sudden changes in upstream voltages, and constant power loads (CPL). The influence of the gain values (K) on the controller was also analyzed. The results show that the controller is robust regarding its sensitivity to external disturbances and steady-state error. However, the importance of the constant “K” in the model states that there exist K-limit values where if “K” is too low, a slowdown is presented, and the response against disturbances can be critical, and if is too high, an overshoot is presented in the output voltage.
Full article
(This article belongs to the Special Issue Control and Optimization of Microgrids and Renewable Energy Systems)
Open AccessReview
Linear, Nonlinear, and Distributed-Parameter Observers Used for (Renewable) Energy Processes and Systems—An Overview
by
Verica Radisavljevic-Gajic, Dimitri Karagiannis and Zoran Gajic
Energies 2024, 17(11), 2700; https://doi.org/10.3390/en17112700 (registering DOI) - 2 Jun 2024
Abstract
Full- and reduced-order observers have been used in many engineering applications, particularly for energy systems. Applications of observers to energy systems are twofold: (1) the use of observed variables of dynamic systems for the purpose of feedback control and (2) the use of
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Full- and reduced-order observers have been used in many engineering applications, particularly for energy systems. Applications of observers to energy systems are twofold: (1) the use of observed variables of dynamic systems for the purpose of feedback control and (2) the use of observers in their own right to observe (estimate) state variables of particular energy processes and systems. In addition to the classical Luenberger-type observers, we will review some papers on functional, fractional, and disturbance observers, as well as sliding-mode observers used for energy systems. Observers have been applied to energy systems in both continuous and discrete time domains and in both deterministic and stochastic problem formulations to observe (estimate) state variables over either finite or infinite time (steady-state) intervals. This overview paper will provide a detailed overview of observers used for linear and linearized mathematical models of energy systems and review the most important and most recent papers on the use of observers for nonlinear lumped (concentrated)-parameter systems. The emphasis will be on applications of observers to renewable energy systems, such as fuel cells, batteries, solar cells, and wind turbines. In addition, we will present recent research results on the use of observers for distributed-parameter systems and comment on their actual and potential applications in energy processes and systems. Due to the large number of papers that have been published on this topic, we will concentrate our attention mostly on papers published in high-quality journals in recent years, mostly in the past decade.
Full article
(This article belongs to the Section B: Energy and Environment)
Open AccessArticle
Microgrid F36ault Detection Method Based on Lightweight Gradient Boosting Machine–Neural Network Combined Modeling
by
Zhiye Lu, Lishu Wang and Panbao Wang
Energies 2024, 17(11), 2699; https://doi.org/10.3390/en17112699 (registering DOI) - 2 Jun 2024
Abstract
The intelligent architecture based on the microgrid (MG) system enhances distributed energy access through an effective line network. However, the increased paths between power sources and loads complicate the system’s topology. This complexity leads to multidirectional line currents, heightening the risk of current
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The intelligent architecture based on the microgrid (MG) system enhances distributed energy access through an effective line network. However, the increased paths between power sources and loads complicate the system’s topology. This complexity leads to multidirectional line currents, heightening the risk of current loops, imbalances, and potential short-circuit faults. To address these challenges, this study proposes a new approach to accurately locate and identify faults based on MG lines. Initially, characteristic indices such as fault voltage, voltage fundamentals at each MG measurement point, and extracted features like peak voltage values in specific frequency bands, phase-to-phase voltage differences, and the sixth harmonic components are utilized as model inputs. Subsequently, these features are classified using the Lightweight Gradient Boosting Machine (LightGBM), complemented by the bagging (Bootstrap Aggregating) ensemble learning algorithm to consolidate multiple strong LightGBM classifiers in parallel. The output classification results of the integrated model are then fed into a neural network (NN) for further training and learning for fault-type identification and localization. In addition, a Shapley value analysis is introduced to quantify the contribution of each feature and visualize the fault diagnosis decision-making process. A comparative analysis with existing methodologies demonstrates that the LightGBM-NN model not only improves fault detection accuracy but also exhibits greater resilience against noise interference. The introduction of the bagging method, by training multiple base models on the initial classification subset of LightGBM and aggregating their prediction results, can reduce the model variance and prevent overfitting, thus improving the stability and accuracy of fault detection in the combined model and making the interpretation of the Shapley value more stable and reliable. The introduction of the Shapley value analysis helps to quantify the contribution of each feature to improve the transparency and understanding of the combined model’s troubleshooting decision-making process, reduces the model’s subsequent collection of data from different line operations, further optimizes the collection of line feature samples, and ensures the model’s effectiveness and adaptability.
Full article
(This article belongs to the Special Issue Latest Advances and Prospects in Microgrids)
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Open AccessArticle
Uncalcined Zn/Al Carbonate LDH and Its Calcined Counterpart for Treating the Wastewater Containing Anionic Congo Red Dye
by
Kuppusamy Manjula Rani, Pachagoundanpalayam Nachimuthugounder Palanisamy, Vennila Nagamuthu Kowshalya, Ayyasamy Tamilvanan, Rajendran Prabakaran and Sung Chul Kim
Energies 2024, 17(11), 2698; https://doi.org/10.3390/en17112698 (registering DOI) - 2 Jun 2024
Abstract
In this investigation, Zn/Al carbonate layered double hydroxide (ZAC-LDH) and its derived material on calcination were synthesized for removing the anionic azo dye Congo red (CR) from wastewater. Numerous factors were methodically investigated, including temperature, adsorbent dosage, pH, starting Dye Concentration (DC), and
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In this investigation, Zn/Al carbonate layered double hydroxide (ZAC-LDH) and its derived material on calcination were synthesized for removing the anionic azo dye Congo red (CR) from wastewater. Numerous factors were methodically investigated, including temperature, adsorbent dosage, pH, starting Dye Concentration (DC), and contact time. The CR elimination percentage dropped as the initial DC increased from 25 mg/L to 100 mg/L at 30 °C for uncalcined LDH, and from 97.96% to 89.25% for calcined LDH. The pH analysis indicates that the highest level of dye removal was recorded within the acidic pH range through the electrostatic attraction mechanism. The sorption kinetics analysis results demonstrated that the pseudo-second-order kinetic model exhibited a stronger fit to both uncalcined LDH and CZA-LDH, with the maximum correlation coefficient value. The Van’t Hoff plots indicate the spontaneous nature of the physisorption process with a negative ΔG° (<−20 kJ/mol), while the endothermic adsorption process exhibited a positive ΔH°. The X-ray diffraction of calcined LDH reveals a significant intercalation of CR dye molecules, both prior to and following adsorption, showcasing a distinctive memory effect. The Brunauer–Emmett–Teller (BET) gas sorption measurements were performed to support the mesoporous nature of ZAC-LDH and CZA-LDH. The FTIR spectrum confirms the interaction of dye molecules on the surface of uncalcined and calcined LDH. These findings emphasize the efficacy of both the synthesized LDHs in removing CR dye, with CZA-LDH demonstrating superior efficiency compared to uncalcined LDH in the context of CR removal from wastewater.
Full article
(This article belongs to the Special Issue Advances in Wastewater Treatment 2024)
Open AccessArticle
Numerical Study of Heat Transfer and Fluid Flow Characteristics of a Hydrogen Pulsating Heat Pipe with Medium Filling Ratio
by
Dongyu Yang, Zhicheng Bu, Bo Jiao, Bo Wang and Zhihua Gan
Energies 2024, 17(11), 2697; https://doi.org/10.3390/en17112697 (registering DOI) - 2 Jun 2024
Abstract
Benefiting from its high thermal conductivity, simple structure, and light weight, the pulsating heat pipe (PHP) can meet the requirements for high efficiency, flexibility, and low cost in industrial heat transfer applications such as aerospace detector cooling and vehicle thermal management. Compared to
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Benefiting from its high thermal conductivity, simple structure, and light weight, the pulsating heat pipe (PHP) can meet the requirements for high efficiency, flexibility, and low cost in industrial heat transfer applications such as aerospace detector cooling and vehicle thermal management. Compared to a PHP working at room temperature, the mechanism of a PHP with hydrogen as the working fluid differs significantly due to the unique thermal properties of hydrogen. In this paper, a two-dimensional model of a hydrogen PHP with a filling ratio of 51% was established to study the flow characteristics and thermal performance. The volume of fluid (VOF) method was used to capture the phase distribution and interface dynamics, and the Lee model was employed to account for phase change. To validate the model, a comparison was conducted between the simulation results and experimental data obtained in our laboratory. The simulation results show that the pressure and temperature errors were within 25% and 5%, respectively. Throughout a pressure oscillation cycle, the occurrence of uniform flow velocity, acceleration, and flow reversal can be attributed to the changes in the vapor–liquid phase distribution resulting from the effect of condensation and evaporation. In addition, when the fluid velocity was greater than 0.6 m/s, dynamic contact angle hysteresis was observed in the condenser. The results contribute to a deeper understanding of the flow and heat transfer mechanism of the hydrogen PHPs, which have not been yet achieved through visualization experiments.
Full article
(This article belongs to the Special Issue Advances in Numerical Modeling of Multiphase Flow and Heat Transfer)
Open AccessArticle
Effect of Plasma Gas Type on the Operation Characteristics of a Three-Phase Plasma Reactor with Gliding Arc Discharge
by
Henryka Danuta Stryczewska, Grzegorz Komarzyniec and Oleksandr Boiko
Energies 2024, 17(11), 2696; https://doi.org/10.3390/en17112696 (registering DOI) - 2 Jun 2024
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Three-phase gliding arc discharge reactors are devices in which it is difficult to maintain stable plasma parameters, be it electrically, physically, or chemically. The main cause of plasma instability is the source, which is freely burning arcs in a three-phase system. In addition,
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Three-phase gliding arc discharge reactors are devices in which it is difficult to maintain stable plasma parameters, be it electrically, physically, or chemically. The main cause of plasma instability is the source, which is freely burning arcs in a three-phase system. In addition, these arcs burn at low currents and are intensively cooled, further increasing their instability. These instabilities translate into the electrical characteristics of the plasma reactor. The analysis for the four gases nitrogen, argon, helium, and air shows that the type of plasma-generating gas and its physical parameters have a strong influence on the operational characteristics of the plasma reactor. Current–voltage, power and frequency characteristics of the plasma reactor were plotted experimentally. Characteristics obtained in this way make it possible to determine the areas of effective operation of the plasma reactor, and to estimate the quality of the generated plasma. Based on the characteristics obtained, a method of controlling the plasma parameters can be developed.
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Open AccessArticle
On the Development of a Near-Shore Pivoting Wave Energy Converter
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Gianmaria Giannini, Esmaeil Zavvar, Victor Ramos, Tomás Calheiros-Cabral, Isabel Iglesias, Francisco Taveira-Pinto and Paulo Rosa-Santos
Energies 2024, 17(11), 2695; https://doi.org/10.3390/en17112695 (registering DOI) - 1 Jun 2024
Abstract
Numerous offshore wave energy converter (WEC) designs have been invented; however, none has achieved full commercialization so far. The primary obstacle impeding WEC commercialization is the elevated levelized cost of energy (LCOE). Consequently, there exists a pressing need to innovate and swiftly diminish
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Numerous offshore wave energy converter (WEC) designs have been invented; however, none has achieved full commercialization so far. The primary obstacle impeding WEC commercialization is the elevated levelized cost of energy (LCOE). Consequently, there exists a pressing need to innovate and swiftly diminish the LCOE. A critical challenge faced by WECs is their susceptibility to extreme wave loads during storms. Promising concepts must demonstrate robust design features to ensure resilience in adverse conditions, while maintaining efficiency in harnessing power under normal sea states. It is anticipated that the initial commercial endeavors will concentrate on near-shore WEC technologies due to the cost advantages associated with proximity to the coastline, facilitating more affordable power transmission and maintenance. In response, this manuscript proposes a pioneering near-shore WEC concept designed with a survivability mode that is engineered to mitigate wave loads during severe sea conditions. Moreover, prior investigations have highlighted favorable resonance properties of this novel concept, enhancing wave power extraction during recurrent energetic sea states. This study employs numerical and physical modelling techniques to evaluate wave loads on the proposed WEC. The results indicate a remarkable 65% reduction in wave loads on the moving floater of the WEC during a range of sea states under the implemented survivability mode.
Full article
(This article belongs to the Special Issue Renewable and Sustainable Energy in Light of Energy Transition Processes)
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Economic Analysis of Solid Oxide Fuel Cell Systems Utilizing Natural Gas as Fuel
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Yantao Yang, Yilin Shen, Tanglei Sun, Peng Liu and Tingzhou Lei
Energies 2024, 17(11), 2694; https://doi.org/10.3390/en17112694 (registering DOI) - 1 Jun 2024
Abstract
Solid oxide fuel cell power generation systems are devices that utilize solid electrolytes to transfer ions for electrochemical energy conversion. A wide range of gases can be used as fuel gas, including hydrogen, natural gas, and carbon monoxide. Considering the high cost of
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Solid oxide fuel cell power generation systems are devices that utilize solid electrolytes to transfer ions for electrochemical energy conversion. A wide range of gases can be used as fuel gas, including hydrogen, natural gas, and carbon monoxide. Considering the high cost of pure hydrogen, hydrogen production from natural gas reforming has become a hot research area. In this study, the 4F-LCA method was employed to construct an evaluation framework, with a particular emphasis on the cost analysis of solid oxide fuel cell power generation systems, and uses a bottom-up approach to build a system economic analysis model to visualize the major costs involved in the system. An economic benefit analysis and sensitivity analysis were carried out for the 2 kW natural gas solid oxide fuel cell as a case by taking the financial net present value (NPV), internal rate of return (IRR) and payback period into account. In this study, the investment cost and payback period of a 2 kW solid oxide fuel cell system are obtained, which can provide a reference for the project construction and operation of solid oxide fuel cell systems.
Full article
(This article belongs to the Special Issue Advances in Marketing Researches for Sustainable Development of Energy Economic)
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Open AccessArticle
Scaling Energy Transfer in Ball Mills: A Scale-Agnostic Approach through a Universal Scaling Constant
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Błażej Doroszuk, Piotr Bortnowski, Maksymilian Ozdoba and Robert Król
Energies 2024, 17(11), 2693; https://doi.org/10.3390/en17112693 (registering DOI) - 1 Jun 2024
Abstract
Ball mills are widely used for size reduction in mineral processing, but effective scaling from laboratory to industrial scale remains challenging. This study introduces a novel scaling constant approach to replicate energy transfer to ore during milling across different scales by adjusting rotational
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Ball mills are widely used for size reduction in mineral processing, but effective scaling from laboratory to industrial scale remains challenging. This study introduces a novel scaling constant approach to replicate energy transfer to ore during milling across different scales by adjusting rotational speed and grinding medium size distribution. The scaling constant encapsulates parameters like the number of balls per working area, rotational speed, and an average ball’s maximum potential and kinetic energies. Experiments were conducted using a laboratory ball mill with interchangeable drum sizes (300, 400, and 500 mm) and a Design of Experiments methodology. Statistical analysis revealed that the scaling constant was more effective at maintaining consistent specific energy and energy per rotation across scales than size reduction, especially in dry milling. Wet milling results showed no significant differences in all metrics across scales. The dominant charge motion shifted from centrifuging to cascading as the mill diameter increased, highlighting the complex scaling dynamics. While the scaling constant shows promise for maintaining energy utilization, additional factors like charge motion and particle breakage mechanisms should be considered. The findings provide insights for improving ball mill design and optimization in mineral processing.
Full article
(This article belongs to the Section K: State-of-the-Art Energy Related Technologies)
Open AccessArticle
Aircraft Taxi Path Optimization Considering Environmental Impacts Based on a Bilevel Spatial–Temporal Optimization Model
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Yuxiu Chen, Liyan Quan and Jian Yu
Energies 2024, 17(11), 2692; https://doi.org/10.3390/en17112692 (registering DOI) - 1 Jun 2024
Abstract
Aircraft taxiing emissions are the main source of carbon dioxide and other pollutant gas emissions during airport ground operations. It is crucial to optimize aircraft taxiing from both spatial and temporal perspectives to improve airport operation efficiency and reduce aviation emissions. In this
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Aircraft taxiing emissions are the main source of carbon dioxide and other pollutant gas emissions during airport ground operations. It is crucial to optimize aircraft taxiing from both spatial and temporal perspectives to improve airport operation efficiency and reduce aviation emissions. In this paper, a bilevel spatial and temporal optimization model of aircraft taxiing is constructed. The upper-level model optimizes the aircraft taxiing path, and the lower-level model optimizes the taxiing start time of the aircraft. By the iterative optimization of the upper- and lower-level interactions, the aviation fuel consumption, flight waiting time, and number of taxiing conflicts are reduced. To improve the calculation accuracy, the depth-first search algorithm is utilized to generate the set of available paths for aircraft during the model solution process, and a model solution method based on the genetic algorithm is constructed. Simulation experiments using Tianjin Binhai International Airport as the research object show that adopting the waiting taxiing strategy can effectively avoid taxiing conflicts and reduce aviation fuel consumption by 753.18 kg and 188.84 kg compared to the available path sets generated using Dijkstra’s algorithm and those created manually based on experience, respectively. Conversely, adopting an immediate taxi-out strategy caused 54 taxiing conflicts and increased aviation fuel consumption by 49.44 kg. These results can provide safe and environmentally friendly taxiing strategies for the sustainable development of the air transportation industry.
Full article
(This article belongs to the Section B: Energy and Environment)
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Open AccessArticle
Impact of Using n-Octanol/Diesel Blends on the Performance and Emissions of a Direct-Injection Diesel Engine
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Jongkap Ahn, Kwonwoo Jang, Jeonghyeon Yang, Beomsoo Kim and Jaesung Kwon
Energies 2024, 17(11), 2691; https://doi.org/10.3390/en17112691 (registering DOI) - 1 Jun 2024
Abstract
This study evaluates the viability of n-octanol as an alternative fuel in a direct-injection diesel engine, aiming to enhance sustainability and efficiency. Experiments fueled by different blends of n-octanol with pure diesel were conducted to analyze their impacts on engine performance and emissions.
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This study evaluates the viability of n-octanol as an alternative fuel in a direct-injection diesel engine, aiming to enhance sustainability and efficiency. Experiments fueled by different blends of n-octanol with pure diesel were conducted to analyze their impacts on engine performance and emissions. The methodology involved testing each blend in a single-cylinder engine, measuring engine performance parameters such as brake torque and brake power under full-load conditions across a range of engine speeds. Comparative assessments of performance and emission characteristics at a constant engine speed were also conducted with varying loads. The results indicated that while n-octanol blends consistently improved brake thermal efficiency, they also increased brake-specific fuel consumption due to the lower energy content of n-octanol. Consequently, while all n-octanol blends reduced nitrogen oxide emissions compared to pure diesel, they also significantly decreased carbon monoxide, hydrocarbons, and smoke opacity, presenting a comprehensive reduction in harmful emissions. However, the benefits came with complex trade-offs: notably, higher concentrations of n-octanol led to a relative increase in nitrogen oxide emissions as the n-octanol ratio increased. The study concludes that n-octanol significantly improves engine efficiency and reduces diesel dependence, but optimizing the blend ratio is crucial to balance performance improvements with comprehensive emission reductions.
Full article
(This article belongs to the Special Issue Internal Combustion Engines for Carbon Neutrality: Performance, Combustion and Emission)
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Open AccessArticle
Energetic, Exergetic, and Techno-Economic Analysis of A Bioenergy with Carbon Capture and Utilization Process via Integrated Torrefaction–CLC–Methanation
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Enrico Alberto Cutillo, Claudio Tregambi, Piero Bareschino, Erasmo Mancusi, Gaetano Continillo and Francesco Pepe
Energies 2024, 17(11), 2690; https://doi.org/10.3390/en17112690 (registering DOI) - 1 Jun 2024
Abstract
Bioenergy with carbon capture and storage (BECCS) or utilization (BECCU) allows net zero or negative carbon emissions and can be a breakthrough technology for climate change mitigation. This work consists of an energetic, exergetic, and economic analysis of an integrated process based on
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Bioenergy with carbon capture and storage (BECCS) or utilization (BECCU) allows net zero or negative carbon emissions and can be a breakthrough technology for climate change mitigation. This work consists of an energetic, exergetic, and economic analysis of an integrated process based on chemical looping combustion of solar-torrefied agro-industrial residues, followed by methanation of the concentrated CO2 stream with green H2. Four agro-industrial residues and four Italian site locations are considered. Depending on the considered biomass, the integrated plant processes about 18–93 kg h−1 of raw biomass and produces 55–70 t y−1 of synthetic methane. Global exergetic efficiencies ranged within 45–60% and 67–77% when neglecting and considering, respectively, the valorization of torgas. Sugar beet pulp and grape marc required a non-negligible input exergy flow for the torrefaction, due to the high moisture content of the raw biomasses. However, for these biomasses, the water released during drying/torrefaction and CO2 methanation could be recycled to the electrolyzer to eliminate external water consumption, thus allowing for a more sustainable use of water resources. For olive stones and hemp hurd, this water recycling brings, instead, a reduction of approximately 65% in water needs. A round-trip electric efficiency of 28% was estimated assuming an electric conversion efficiency of 40%. According to the economic analysis, the total plant costs ranged within 3–5 M€ depending on the biomass and site location considered. The levelized cost of methane (LCOM) ranged within 4.3–8.9 € kgCH4−1 but, if implementing strategies to avoid the use of a large temporary H2 storage vessel, can be decreased to 2.6–5.3 € kgCH4−1. Lower values are obtained when considering hemp hurd and grape marc as raw biomasses, and when locating the PV field in the south of Italy. Even in the best scenario, values of LCOM are out of the market if compared to current natural gas prices, but they might become competitive with the introduction of a carbon tax or through government incentives for the purchase of the PV field and/or electrolyzer.
Full article
(This article belongs to the Section A: Sustainable Energy)
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Open AccessArticle
Empirical Assessment of the Efficiency of Poland’s Energy Transition Process in the Context of Implementing the European Union’s Energy Policy
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Jarosław Brodny, Magdalena Tutak and Wes Grebski
Energies 2024, 17(11), 2689; https://doi.org/10.3390/en17112689 (registering DOI) - 1 Jun 2024
Abstract
This article addresses one of the contemporary economy’s most challenging endeavors: the energy transition. Specifically, the aim of the study was to assess the effectiveness of Poland’s energy transition process between 2004 and 2021. A comprehensive approach is employed to analyze Poland’s energy
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This article addresses one of the contemporary economy’s most challenging endeavors: the energy transition. Specifically, the aim of the study was to assess the effectiveness of Poland’s energy transition process between 2004 and 2021. A comprehensive approach is employed to analyze Poland’s energy transition process, focusing on the effectiveness of implementation through the Energy Transition Effectiveness Index. This methodology incorporates four dimensions, namely energy security, economic considerations, climate impact, and social aspects, each characterized by 22 sub-indices. The research methodology employs a two-tiered approach based on the multi-criteria decision making methodology. The EDAS method is utilized to determine the indices’ values, while the CRITIC, equal weights, and statistical variance methods and Laplace’s criterion are employed to ascertain sub-indices values and dimension weights, particularly useful for decision making under uncertainty. Moreover, the relationship between these indices, the Energy Transition Effectiveness Index, and Poland’s Gross Domestic Product is explored. By evaluating Poland’s energy transition effectiveness from 2004 to 2021 and comparing the results with other European Union countries, it becomes evident that the effectiveness varies over time. Despite encountering economic and social challenges during the energy sector’s transformation, Poland exhibits positive progress in its energy transition efforts, outperforming certain European Union counterparts. However, there is a pressing need to intensify efforts to curtail emissions and enhance renewable energy utilization. The European Union’s support and coordination are deemed crucial in facilitating these endeavors, alongside fostering the wider adoption of best practices among member states. The developed methodology stands as a valuable tool for ongoing evaluation of transformation processes across European Union nations.
Full article
(This article belongs to the Collection Energy Transition towards Carbon Neutrality)
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The Impact of Energy Efficiency on Economic Growth: Application of the MARCO Model to the Portuguese Economy 1960–2014
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João Santos, Miguel Viana, Jaime Nieto, Paul E. Brockway, Marco Sakai and Tiago Domingos
Energies 2024, 17(11), 2688; https://doi.org/10.3390/en17112688 (registering DOI) - 1 Jun 2024
Abstract
The benefits of energy efficiency are recognized in multiple socio-economic spheres. Still, the quantitative impact on macroeconomic performance is not fully understood, as modeling tools are not thermodynamically consistent—failing to explicitly include the useful stage of energy flows and/or thermodynamic efficiencies in primary–final–useful
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The benefits of energy efficiency are recognized in multiple socio-economic spheres. Still, the quantitative impact on macroeconomic performance is not fully understood, as modeling tools are not thermodynamically consistent—failing to explicitly include the useful stage of energy flows and/or thermodynamic efficiencies in primary–final–useful energy transformations. Misspecification in the link between energy use and the economy underplays the role of energy use and efficiency in economic growth. In this work, we develop and implement the Macroeconometric Resource Consumption model for Portugal (MARCO-PT), 1960–2014. Based on the post-Keynesian framework developed for the United Kingdom (MARCO-UK), our model explicitly includes thermodynamic energy efficiency, extending the analysis to the useful stage of energy flows. The model’s stochastic equations are econometrically estimated. The historical influence of key variables—namely thermodynamic energy efficiency—on economic output is assessed through counterfactual simulations and computation of year-by-year output elasticities. The MARCO-PT model adequately describes the historical behavior of endogenous variables. Although its influence has decreased over time, thermodynamic efficiency has consistently been the major contributor to economic growth between 1960–2014, with an average output elasticity of 0.46. Total useful exergy is also a major contributing factor, with an average output elasticity of 0.29. Both have a higher influence than capital, labor, or other energy variables (final energy, prices). An adequate integration of thermodynamic efficiency is thus crucial for macroeconomic models.
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(This article belongs to the Section C: Energy Economics and Policy)
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Open AccessArticle
Enhanced Day-Ahead Electricity Price Forecasting Using a Convolutional Neural Network–Long Short-Term Memory Ensemble Learning Approach with Multimodal Data Integration
by
Ziyang Wang, Masahiro Mae, Takeshi Yamane, Masato Ajisaka, Tatsuya Nakata and Ryuji Matsuhashi
Energies 2024, 17(11), 2687; https://doi.org/10.3390/en17112687 (registering DOI) - 1 Jun 2024
Abstract
Day-ahead electricity price forecasting (DAEPF) holds critical significance for stakeholders in energy markets, particularly in areas with large amounts of renewable energy sources (RES) integration. In Japan, the proliferation of RES has led to instances wherein day-ahead electricity prices drop to nearly zero
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Day-ahead electricity price forecasting (DAEPF) holds critical significance for stakeholders in energy markets, particularly in areas with large amounts of renewable energy sources (RES) integration. In Japan, the proliferation of RES has led to instances wherein day-ahead electricity prices drop to nearly zero JPY/kWh during peak RES production periods, substantially affecting transactions between electricity retailers and consumers. This paper introduces an innovative DAEPF framework employing a Convolutional Neural Network–Long Short-Term Memory (CNN–LSTM) model designed to predict day-ahead electricity prices in the Kyushu area of Japan. To mitigate the inherent uncertainties associated with neural networks, a novel ensemble learning approach is implemented to bolster the DAEPF model’s robustness and prediction accuracy. The CNN–LSTM model is verified to outperform a standalone LSTM model in both prediction accuracy and computation time. Additionally, applying a natural logarithm transformation to the target day-ahead electricity price as a pre-processing technique has proven necessary for higher prediction accuracy. A novel "policy-versus-policy" strategy is proposed to address the prediction problem of the zero prices, halving the computation time of the traditional two-stage method. The efficacy of incorporating a suite of multimodal features: areal day-ahead electricity price, day-ahead system electricity price, areal actual power generation, areal meteorological forecasts, calendar forecasts, alongside the rolling features of areal day-ahead electricity price, as explanatory variables to significantly enhance DAEPF accuracy has been validated. With the full integration of the proposed features, the CNN–LSTM ensemble model achieves its highest accuracy, reaching performance metrics of , MAE, and RMSE of 0.787, 1.936 JPY/kWh, and 2.630 JPY/kWh, respectively, during the test range from 1 March 2023 to 31 March 2023, underscoring the advantages of a comprehensive, multi-dimensional approach to DAEPF.
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(This article belongs to the Section C: Energy Economics and Policy)
Open AccessArticle
Intelligent Learning Method for Capacity Estimation of Lithium-Ion Batteries Based on Partial Charging Curves
by
Can Ding, Qing Guo, Lulu Zhang and Tao Wang
Energies 2024, 17(11), 2686; https://doi.org/10.3390/en17112686 - 31 May 2024
Abstract
Lithium-ion batteries are widely used in electric vehicles, energy storage power stations, and many other applications. Accurate and reliable monitoring of battery health status and remaining capacity is the key to establish a lithium-ion cell management system. In this paper, based on a
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Lithium-ion batteries are widely used in electric vehicles, energy storage power stations, and many other applications. Accurate and reliable monitoring of battery health status and remaining capacity is the key to establish a lithium-ion cell management system. In this paper, based on a Bayesian optimization algorithm, a deep neural network is structured to evaluate the whole charging curve of the battery using partial charging curve data as input. A 0.74 Ah battery is used for experiments, and the effect of different input data lengths is also investigated to check the high flexibility of the approach. The consequences show that using only 20 points of partial charging data as input, the whole charging profile of a cell can be exactly predicted with a root-mean-square error (RMSE) of less than 19.16 mAh (2.59% of the nominal capacity of 0.74 Ah), and its mean absolute percentage error (MAPE) is less than 1.84%. In addition, critical information including battery state-of-charge (SOC) and state-of-health (SOH) can be extracted in this way to provide a basis for safe and long-lasting battery operation.
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(This article belongs to the Special Issue Advances in Modeling Methods for Battery Life Prediction and Performance Evaluation (Volume II))
Open AccessArticle
Lithium Supply Chain Optimization: A Global Analysis of Critical Minerals for Batteries
by
Erick C. Jones, Jr.
Energies 2024, 17(11), 2685; https://doi.org/10.3390/en17112685 - 31 May 2024
Abstract
Energy storage is a foundational clean energy technology that can enable transformative technologies and lower carbon emissions, especially when paired with renewable energy. However, clean energy transition technologies need completely different supply chains than our current fuel-based supply chains. These technologies will instead
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Energy storage is a foundational clean energy technology that can enable transformative technologies and lower carbon emissions, especially when paired with renewable energy. However, clean energy transition technologies need completely different supply chains than our current fuel-based supply chains. These technologies will instead require a material-based supply chain that extracts and processes massive amounts of minerals, especially critical minerals, which are classified by how essential they are for the modern economy. In order to develop, operate, and optimize the new material-based supply chain, new decision-making frameworks and tools are needed to design and navigate this new supply chain and ensure we have the materials we need to build the energy system of tomorrow. This work creates a flexible mathematical optimization framework for critical mineral supply chain analysis that, once provided with exogenously supplied projections for parameters such as demand, cost, and carbon intensity, can provide an efficient analysis of a mineral or critical mineral supply chain. To illustrate the capability of the framework, this work also conducts a case study investigating the global lithium supply chain needed for energy storage technologies like electric vehicles (EVs). The case study model explores the investment and operational decisions that a global central planner would consider in order to meet projected lithium demand in one scenario where the objective is to minimize cost and another scenario where the objective is to minimize emissions. The case study shows there is a 6% cost premium to reduce emissions by 2%. Furthermore, the Objective scenario invested in recycling capacity to reduce emissions, while the Cost Objective scenario did not. Lastly, this case study shows that even with a deterministic model and a global central planner, asset utilization is not perfect, and there is a substantial tradeoff between cost and emissions. Therefore, this framework—when expanded to less-idealized scenarios, like those focused on individual countries or regions or scenarios that optimize other important evaluation metrics—would yield even more impactful insights. However, even in its simplest form, as presented in this work, the framework illustrates its power to model, optimize, and illustrate the material-based supply chains needed for the clean energy technologies of tomorrow.
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(This article belongs to the Section D2: Electrochem: Batteries, Fuel Cells, Capacitors)
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A Practical Superconducting DC Dynamo for Charging Conduction-Cooled HTS Magnet
by
Yujia Zhai, Chunran Mu, Jinduo Wang, Litong Zhu, Tingkun Weng, Zhuo Li, Xingzheng Wu, Liufei Shen, Jianhua Liu and Qiuliang Wang
Energies 2024, 17(11), 2684; https://doi.org/10.3390/en17112684 - 31 May 2024
Abstract
At present, HTS magnets cannot operate in the real closed-loop persistent current mode due to the existence of joint resistance, flux creep, and AC loss of the HTS tape. Instead of using a current source, HTS flux pumps are capable of injecting flux
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At present, HTS magnets cannot operate in the real closed-loop persistent current mode due to the existence of joint resistance, flux creep, and AC loss of the HTS tape. Instead of using a current source, HTS flux pumps are capable of injecting flux into closed HTS magnets without electrical contact. This paper presents a practical superconducting DC dynamo for charging a conduction-cooled HTS magnet system based on a flux-pumping technique. To minimize heat losses, the rotor is driven by a servo motor mounted outside the vacuum dewar by utilizing magnetic fluid dynamic sealing. Different parameters, such as air gap and rotating speed, have been tested to investigate the best pumping effect, and finally, it successfully powers a 27.3 mH HTS non-insulated double-pancake coil to the current of 54.2 A within 76 min. As a low-cost and compact substitute for the traditional current source, the realization of a contactless DC power supply can significantly improve the flexibility and mobility of the HTS magnet system and could be of great significance for the technological innovation of future HTS magnets used in offshore wind turbines, biomedical, aerospace, etc.
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(This article belongs to the Special Issue Emerging Trends in Superconductivity for Electric Power Technologies)
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