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
Real-Time Co-Simulation and Grid Integration of PMSG-Based Hydrokinetic Energy Conversion Systems via Power-Hardware-in-the-Loop Technics
Energies 2024, 17(11), 2662; https://doi.org/10.3390/en17112662 (registering DOI) - 30 May 2024
Abstract
Ocean energy sources are a promising source of energy. However, simulating a hydrokinetic farm with multiple units requires significant computational resources, while physical experimentation on site is expensive. Therefore, the scientific challenge is to develop analytical and experimental tools that consider real aspects
[...] Read more.
Ocean energy sources are a promising source of energy. However, simulating a hydrokinetic farm with multiple units requires significant computational resources, while physical experimentation on site is expensive. Therefore, the scientific challenge is to develop analytical and experimental tools that consider real aspects of areas with generation potential in a controlled laboratory environment. This paper presents a theoretical and experimental tool for analysing the interconnection of a hydrokinetic energy farm comprising 20 generation units. The test bench is a Power Hardware in the Loop type, consisting of one physical prototype generator to scale and 19 discrete averaged models operating in real-time. The system allows generators to interact through an amplifier, emulating the impact of power injection in a small electrical network. This is based on the variability of the marine resource, specifically the current velocities in the Cozumel-Mexico channel. Unlike other publications, the most significant contribution of this work is a complete feasible emulation of a marine current plant interconnected to an electrical grid, where the objective is to have a global analysis of the operation of each generation unit and the impact of the interconnection as a whole, considering that such information is of utmost importance for the execution of future projects of power generation from the sea.
Full article
(This article belongs to the Special Issue Energy Storage Technologies for Grid Forming Systems)
►
Show Figures
Open AccessArticle
Mixed Riccati–Lyapunov Balanced Truncation for Order Reduction of Electrical Circuit Systems
by
Huy-Du Dao, Thanh-Tung Nguyen, Ngoc-Kien Vu, Hong-Son Vu and Hong-Quang Nguyen
Energies 2024, 17(11), 2661; https://doi.org/10.3390/en17112661 (registering DOI) - 30 May 2024
Abstract
This paper proposes a novel algorithm, termed Mixed Riccati–Lyapunov Balanced Truncation (MRLBT), tailored for order reduction of Linear Time-Invariant Continuous-Time Descriptor Systems (LTI-CTD), commonly encountered in electrical and electronic circuit modeling. The MRLBT approach synergistically combines the advantages of balanced truncation (BT) and
[...] Read more.
This paper proposes a novel algorithm, termed Mixed Riccati–Lyapunov Balanced Truncation (MRLBT), tailored for order reduction of Linear Time-Invariant Continuous-Time Descriptor Systems (LTI-CTD), commonly encountered in electrical and electronic circuit modeling. The MRLBT approach synergistically combines the advantages of balanced truncation (BT) and positive-real balanced truncation (PRBT) techniques while mitigating their limitations. Unlike BT, which preserves stability but not passivity, and PRBT, which retains passivity at the expense of larger reduction errors, MRLBT ensures the preservation of both stability and passivity inherent in the original system. Additionally, MRLBT achieves reduced computational complexity and minimized order reduction errors compared to PRBT. The proposed algorithm transforms the system into an equivalent Mixed Riccati–Lyapunov Balanced form, enabling the construction of a reduced-order model that retains the critical physical properties. Theoretical analysis and proofs are provided, establishing an upper bound on the global order reduction error. The efficacy of MRLBT is demonstrated through a numerical example involving an RLC ladder network, showcasing its superior performance over BT and PRBT in terms of reduced errors in the time and frequency domains.
Full article
(This article belongs to the Section F: Electrical Engineering)
►▼
Show Figures
Figure 1
Open AccessArticle
Fault-Tolerant Direct Torque Control of Five-Phase Permanent Magnet Synchronous Motor under Single Open-Phase Fault Based on Virtual Vectors
by
Changpan Zhou, Rundong Zhong, Guodong Sun, Dongdong Zhao, Xiaopeng Zhao and Guoxiu Jing
Energies 2024, 17(11), 2660; https://doi.org/10.3390/en17112660 (registering DOI) - 30 May 2024
Abstract
In the existing literature, direct torque control (DTC) by synthesizing virtual vectors can effectively suppress low-order harmonic currents under the single open-phase fault (OPF) of the five-phase permanent magnet synchronous motor (PMSM), but the sectors and the look-up tables need to be redesigned,
[...] Read more.
In the existing literature, direct torque control (DTC) by synthesizing virtual vectors can effectively suppress low-order harmonic currents under the single open-phase fault (OPF) of the five-phase permanent magnet synchronous motor (PMSM), but the sectors and the look-up tables need to be redesigned, which makes the control process more complicated. In order to solve this problem, an indirect correction method of virtual vectors is proposed, and the amplitudes of the virtual vectors are maximized. The fault-tolerant DTC strategy under the OPF ensures that there is no need to re-divide the sectors under the fault. And the selection rules of the look-up tables are consistent with the healthy operation. The difference is that the amplitudes of ten virtual vectors in the faulty operation are reduced, which simplifies the control process and is easy to implement. Finally, the correctness and effectiveness of the proposed control strategy were verified by experiments.
Full article
(This article belongs to the Special Issue Advanced Topologies and Control Strategies in Electric Machines and Drives)
►▼
Show Figures
Figure 1
Open AccessArticle
Integrated Approach to Reservoir Simulations for Evaluating Pilot CO2 Injection in a Depleted Naturally Fractured Oil Field On-Shore Europe
by
Milan Pagáč, Vladimír Opletal, Anton Shchipanov, Anders Nermoen, Roman Berenblyum, Ingebret Fjelde and Jiří Rez
Energies 2024, 17(11), 2659; https://doi.org/10.3390/en17112659 (registering DOI) - 30 May 2024
Abstract
Carbon dioxide capture and storage (CCS) is a necessary requirement for high-emitting CO2 industries to significantly reduce volumes of greenhouse gases released into the atmosphere and mitigate climate change. Geological CO2 storage into depleted oil and gas fields is the fastest
[...] Read more.
Carbon dioxide capture and storage (CCS) is a necessary requirement for high-emitting CO2 industries to significantly reduce volumes of greenhouse gases released into the atmosphere and mitigate climate change. Geological CO2 storage into depleted oil and gas fields is the fastest and most accessible option for CCS deployment allowing for re-purposing existing infrastructures and utilizing significant knowledge about the subsurface acquired during field production operations. The location of such depleted fields in the neighborhoods of high-emitting CO2 industries is an additional advantage of matured on-shore European fields. Considering these advantages, oil and gas operators are now evaluating different possibilities for CO2 sequestration projects for the fields approaching end of production. This article describes an integrated approach to reservoir simulations focused on evaluating a CO2 injection pilot at one of these matured fields operated by MND and located in the Czech Republic. The CO2 injection site in focus is a naturally fractured carbonate reservoir. This oil-bearing formation has a gas cap and connection to a limited aquifer and was produced mainly by pressure depletion with limited pressure support from water injection. The article summarizes the results of the efforts made by the multi-disciplinary team. An integrated approach was developed starting from geological modeling of a naturally fractured reservoir, integrating the results of laboratory studies and their interpretations (geomechanics and geochemistry), dynamic field data analysis (pressure transient analysis, including time-lapse) and history matching reservoir model enabling simulation of the pilot CO2 injection. The laboratory studies and field data analysis provided descriptions of stress-sensitive fracture properties and safe injection envelope preventing induced fracturing. The impact of potential salt precipitation in the near wellbore area was also included. These effects are considered in the context of a pilot CO2 injection and addressed in the reservoir simulations of injection scenarios. Single-porosity and permeability reservoir simulations with a dominating fracture flow and black-oil formulation with CO2 simulated as a solvent were performed in this study. The arguments for the choice of the simulation approach for the site in focus are shortly discussed. The reservoir simulations indicated a larger site injection capacity than that required for the pilot injection, and gravity-driven CO2 migration pathway towards the gas cap in the reservoir. The application of the approach to the site in focus also revealed large uncertainties, related to fracture description and geomechanical evaluations, resulting in an uncertain safe injection envelope. These uncertainties should be addressed in further studies in preparation for the pilot. The article concludes with an overview of the outcomes of the integrated approach and its application to the field in focus, including a discussion of the issues and uncertainties revealed.
Full article
(This article belongs to the Section H: Geo-Energy)
►▼
Show Figures
Figure 1
Open AccessArticle
A Combined Model of Convolutional Neural Network and Bidirectional Long Short-Term Memory with Attention Mechanism for Load Harmonics Forecasting
by
Excellence M. Kuyumani, Ali N. Hasan and Thokozani C. Shongwe
Energies 2024, 17(11), 2658; https://doi.org/10.3390/en17112658 - 30 May 2024
Abstract
In the increasingly complex and dynamic electrical power system, forecasting harmonics is key to developing and ensuring a clean power supply. The traditional methods have achieved some degree of success. However, they often fail to forecast complex and dynamic harmonics, highlighting the serious
[...] Read more.
In the increasingly complex and dynamic electrical power system, forecasting harmonics is key to developing and ensuring a clean power supply. The traditional methods have achieved some degree of success. However, they often fail to forecast complex and dynamic harmonics, highlighting the serious need to improve the forecasting performance. Precise forecasting of electrical power system harmonics is challenging and demanding, owing to the increased frequency with harmonic noise. The occurrence of harmonics is stochastic in nature; it has taken a long time for the development of dependable and efficient models. Several machine learning and statistical methods have produced positive results with minimal errors. To improve the prognostic accuracy of the power supply system, this study proposes an organic hybrid combination of a convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) with the attention mechanism (AM) method (CNN-BiLSTM-AM) to forecast load harmonics. CNN models intricate non-linear systems with multi-dimensionality aspects. LSTM performs better when dealing with exploding gradients in time series data. Bi-LSTM has two LSTM layers: one layer processes data in the onward direction and the other in the regressive direction. Bi-LSTM uses both preceding and subsequent data, and as a result, it has better performance compared to RNN and LSTM. AM’s purpose is to make desired features outstanding. The CNN-BiLSTM-AM method performed better than the other five methods, with a prediction accuracy of 92.366% and a root mean square error (RMSE) of 0.000000222.
Full article
(This article belongs to the Section F: Electrical Engineering)
►▼
Show Figures
Figure 1
Open AccessArticle
Experimental Investigation on Heat Transfer Enhancement of Phase Change Materials by Fractal Fins
by
Zishuo Guo, Li Xu, Feihu Sun and Si Sun
Energies 2024, 17(11), 2657; https://doi.org/10.3390/en17112657 - 30 May 2024
Abstract
The low thermal conductivity of phase change materials restricts their application fields such as thermal storage and electronic equipment cooling. In order to enhance the heat charging capacity of the phase change unit, fractal fins inspired by plant leaves were designed and manufactured.
[...] Read more.
The low thermal conductivity of phase change materials restricts their application fields such as thermal storage and electronic equipment cooling. In order to enhance the heat charging capacity of the phase change unit, fractal fins inspired by plant leaves were designed and manufactured. The changes in the solid–liquid interface, temperature distribution and liquid fraction in the phase change units with fractal fins during melting were investigated experimentally and compared units with the conventional rectangular fin. The results show that fractal fins have better heat transfer enhancement effects than rectangular fins because the enhancement of heat conduction exceeds the suppression of natural convection. Increasing the number of fins can also shorten the melting time and make the temperature distribution more uniform. Compared with the one rectangular fin unit, the full melting time of the unit with three fractal fins is reduced by 17.07%, and the bottom surface temperature is reduced by 27.47%. However, increasing the number of fins while using tree-like fractal fins may cause the fins to inhibit natural convection more than enhance heat conduction. The research in this paper will provide a better understanding of the melting process of phase change units with fins and provide data for future numerical simulations.
Full article
(This article belongs to the Special Issue Advanced Applications of Solar and Thermal Storage Energy)
►▼
Show Figures
Figure 1
Open AccessArticle
Continuum Modeling of Slightly Wet Fluidization with Electrical Capacitance Tomograph Validation
by
Yassir Makkawi, Xi Yu, Raffaella Ocone and Sotos Generalis
Energies 2024, 17(11), 2656; https://doi.org/10.3390/en17112656 - 30 May 2024
Abstract
Gas–solid fluidized bed reactors are widely used in the power generation industry. The critical effect of the presence of liquid phase, either as a result of heat, chemical reaction or physical interaction, on the hydrodynamics of the reactor is well recognized by academic
[...] Read more.
Gas–solid fluidized bed reactors are widely used in the power generation industry. The critical effect of the presence of liquid phase, either as a result of heat, chemical reaction or physical interaction, on the hydrodynamics of the reactor is well recognized by academic researchers and industrial operators. However, theory and simulation frameworks to predict such a condition using the continuum modeling approach are not yet available. This study first shows the significant changes in the flow pattern and distinguishable flow regimes in a slightly wet fluidized bed recorded by an advanced imaging technique. The study then describes the development and implementation of new mathematical formulations for wet particle-particle interactions in a continuum model based on the classic kinetic theory of granular flow (KTGF). Quantitative validation, carried out by comparing the predicted and measured fluidization index (FI) expressed in terms of pressure drop, has shown a good match. The prediction also demonstrates increased bubble splitting, gas channeling, slugging fluidization, and energy dissipation induced by liquid bridges developing from wet particle interactions. These characteristics are similar to those commonly observed in the fluidization of cohesive powders. This model constitutes an important step in extending the continuum theories of dry flow to wet particle-particle interactions. This will allow accurate description and simulation of the fluidized bed in its widest application including power generation systems that involve wet particle fluidization.
Full article
(This article belongs to the Section A: Sustainable Energy)
►▼
Show Figures
Figure 1
Open AccessArticle
Predicting Gas Separation Efficiency of a Downhole Separator Using Machine Learning
by
Ashutosh Sharma, Laura Camila Osorio Ojeda, Na Yuan, Tunc Burak, Ishank Gupta, Nabe Konate and Hamidreza Karami
Energies 2024, 17(11), 2655; https://doi.org/10.3390/en17112655 - 30 May 2024
Abstract
Artificial lift systems, such as electrical submersible pumps and sucker rod pumps, frequently encounter operational challenges due to high gas–oil ratios, leading to premature tool failure and increased downtime. Effective upstream gas separation is critical to maintain continuous operation. This study aims to
[...] Read more.
Artificial lift systems, such as electrical submersible pumps and sucker rod pumps, frequently encounter operational challenges due to high gas–oil ratios, leading to premature tool failure and increased downtime. Effective upstream gas separation is critical to maintain continuous operation. This study aims to predict the efficiency of downhole gas separator using machine learning models trained on data from a centrifugal separator and tested on data from a gravity separator (blind test). A comprehensive experimental setup included a multiphase flow system with horizontal (31 ft. (9.4 m)) and vertical (27 ft. (8.2 m)) sections to facilitate the tests. Seven regression models—multilinear regression, random forest, support vector machine, ridge, lasso, k-nearest neighbor, and XGBoost—were evaluated using performance metrics like RMSE, MAPE, and R-squared. In-depth exploratory data analysis and data preprocessing identified inlet liquid and gas volume flows as key predictors for gas volume flow per minute at the outlet (GVFO). Among the models, random forest was most effective, exhibiting an R-squared of 96% and an RMSE of 112. This model, followed by KNN, showed great promise in accurately predicting gas separation efficiency, aided by rigorous hyperparameter tuning and cross-validation to prevent overfitting. This research offers a robust machine learning workflow for predicting gas separation efficiency across different types of downhole gas separators, providing valuable insights for optimizing the performance of artificial lift systems.
Full article
(This article belongs to the Special Issue Recent Advances in Oil and Gas Recovery and Production Optimisation)
►▼
Show Figures
Figure 1
Open AccessArticle
The Influence of the Mining Operation Environment on the Energy Consumption and Technical Availability of Truck Haulage Operations in Surface Mines
by
Przemysław Bodziony and Michał Patyk
Energies 2024, 17(11), 2654; https://doi.org/10.3390/en17112654 - 30 May 2024
Abstract
This paper presents an analysis of the impact of selected parameters of the operating environment on the energy consumption and reliability of haulage in surface mining. The analysis is based on a cyclic haulage system in a limestone open pit. The results of
[...] Read more.
This paper presents an analysis of the impact of selected parameters of the operating environment on the energy consumption and reliability of haulage in surface mining. The analysis is based on a cyclic haulage system in a limestone open pit. The results of the calculations show that maintaining the operating environment in good technical condition has a positive effect on the haulage process and a direct or indirect effect on the operating costs, the analysis of which is also presented in the main body of the article. The analysis was carried out for a full year’s production, taking into account actual operating and maintenance downtime. The results of similar analyses can be used as a basis for deciding on the type of truck to be used for transport or for reconfiguring transport routes. In addition to the economic and operational aspects of energy consumption and reliability, the environmental aspect cannot be overlooked. The comparison of two variants of mining conditions shows that a modification of the haul road surface leads to a significant reduction in fuel consumption. Depending on the type of vehicle, fuel consumption can be reduced by almost 20%. The potential reduction in fuel consumption directly translates into lower exhaust emissions, which is an important element of an environmentally sustainable approach to mining transport, and greater reliability increases efficiency and reduces the carbon footprint of the vehicle.
Full article
(This article belongs to the Section B: Energy and Environment)
►▼
Show Figures
Figure 1
Open AccessReview
Financial Investment Valuation Models for Photovoltaic and Energy Storage Projects: Trends and Challenges
by
Angela María Gómez-Restrepo, Juan David González-Ruiz and Sergio Botero Botero
Energies 2024, 17(11), 2653; https://doi.org/10.3390/en17112653 - 30 May 2024
Abstract
Energy production through non-conventional renewable sources allows progress towards meeting the Sustainable Development Objectives and constitutes abundant and reliable sources when combined with storage systems. From a financial viewpoint, renewable energy production projects withstand significant challenges such as competition, irreversibility of investments, high
[...] Read more.
Energy production through non-conventional renewable sources allows progress towards meeting the Sustainable Development Objectives and constitutes abundant and reliable sources when combined with storage systems. From a financial viewpoint, renewable energy production projects withstand significant challenges such as competition, irreversibility of investments, high uncertainty levels, and considerable investment amounts. These facts make their financial valuation fundamental for all the agents involved. Using the Web of Science (WoS) and Scopus databases, a scientometric analysis was carried out to understand the methods that have been used in the financial appraisal of photovoltaic energy generation projects with storage systems. The present research project was developed from 268 studies published between 2013 and 2023; tools such as Bibliometrix 4.1.3, VOSViewer 1.6.19, and Tree of Science 0.0.1a9 were used. Two main findings stand out: (i) the most used methods in the literature are the traditional ones, and within them, the levelized cost of energy has been used with greater frequency; and (ii) there is an interest in analyzing the investments of these systems for residences within the framework of distributed energy generation. Two gaps were found in the literature: (i) the studies that were carried out have not comprehensively incorporated the financial challenges faced by these investments; and (ii) the evaluation of these projects has not been addressed from the perspective of a utility-based power generator.
Full article
(This article belongs to the Special Issue Advances in Solar Systems and Energy Efficiency)
►▼
Show Figures
Figure 1
Open AccessArticle
Economic Consequences Based on Reversible and Irreversible Degradation of PV Park in the Harsh Climate Conditions of Iraq
by
Mohammed Adnan Hameed, David Daßler, Qais Matti Alias, Roland Scheer and Ralph Gottschalg
Energies 2024, 17(11), 2652; https://doi.org/10.3390/en17112652 - 30 May 2024
Abstract
Photovoltaic (PV) system reliability and durability investigations are essential for industrial maturity and economic success. Recently, PV systems received much interest in Iraq due to many reasons—for instance, power shortage, global warming and pollution. Despite this interest, the precise economic implications of PV
[...] Read more.
Photovoltaic (PV) system reliability and durability investigations are essential for industrial maturity and economic success. Recently, PV systems received much interest in Iraq due to many reasons—for instance, power shortage, global warming and pollution. Despite this interest, the precise economic implications of PV system reliability in harsh climates like Iraq remain uncertain. This work assesses the economic implications of PV system component reliability and soiling in Iraq using field experience and historical data. This study identifies the most common failure modes of PV systems installed in Iraq and similar climatic regions, and also ranks their severity. Simulations explore scenarios of PV module degradation rates, inverter lifetimes, soiling rates, and cleaning intervals, revealing that soiling has the most detrimental effect, with cleaning frequency leading to Levelized Cost of Electricity (LCOE) losses of over 30%, depending on the location. Inverter lifetime contributes to LCOE losses between 4 and 6%, depending on the PV system’s location. This study also evaluates the impact of tilt angle as a mitigation strategy for reducing soiling loss and its economic implications, finding that installing PV modules at higher tilt angles could reduce the economic impact of soiling by approximately 4.4%. Additionally, the optimal cleaning strategy identified is fully automated dry cleaning with robots, outperforming other strategies economically. Overall, the findings highlight that the LCOE in Iraq is relatively high compared to the global weighted average for utility-scale PV systems, primarily due to high soiling and degradation rates. The LCOE varies within the country, influenced by different degradation rates. This study aims to assist PV stakeholders in Iraq and the Middle East and North Africa (MENA) region in accurately estimating solar bankability; moreover, increasing reliability by minimizing the technical and financial risks by considering key parameters specific to these regions.
Full article
(This article belongs to the Section A2: Solar Energy and Photovoltaic Systems)
►▼
Show Figures
Figure 1
Open AccessArticle
Investigation of SiC MOSFET Body Diode Reverse Recovery and Snappy Recovery Conditions
by
Giuseppe Pennisi, Mario Pulvirenti, Luciano Salvo, Angelo Giuseppe Sciacca, Salvatore Cascino, Antonio Laudani, Nunzio Salerno and Santi Agatino Rizzo
Energies 2024, 17(11), 2651; https://doi.org/10.3390/en17112651 - 30 May 2024
Abstract
This paper investigates the behavior of SiC MOSFETs body diode reverse recovery as a function of different operating conditions. The knowledge of their effects is crucial to properly designing and driving power converters based on SiC devices, in order to optimize the MOSFETs
[...] Read more.
This paper investigates the behavior of SiC MOSFETs body diode reverse recovery as a function of different operating conditions. The knowledge of their effects is crucial to properly designing and driving power converters based on SiC devices, in order to optimize the MOSFETs commutations aiming at improving efficiency. Indeed, reverse recovery is a part of the switching transient, but it has a significant role due to its impact on recovery energy and charge. The set of different operating conditions has been properly chosen to prevent or force the snappy recovery of the device under testing. The experimental results and specific software simulations have revealed phenomena unknown in the literature. More specifically, the analysis of the reverse recovery charge, Qrr, revealed two unexpected phenomena at high temperatures: it decreased with increasing gate voltage; the higher the device threshold, the higher the Qrr. TCAD-Silvaco (ATLAS v. 5.29.0.C) simulations have shown that this is due to a displacement current flowing in the drift region due to the output capacitance voltage variation during commutation. From the analysis of the snappy recovery, it has emerged that there is a minimum forward current slope, below which the reverse recovery cannot be snappy, even for a high current level. Once this current slope is reached, Qrr varies with the forward current only.
Full article
(This article belongs to the Section F3: Power Electronics)
►▼
Show Figures
Figure 1
Open AccessReview
Biofuels in Aviation: Exploring the Impact of Sustainable Aviation Fuels in Aircraft Engines
by
Ramozon Khujamberdiev and Haeng Muk Cho
Energies 2024, 17(11), 2650; https://doi.org/10.3390/en17112650 - 30 May 2024
Abstract
This comprehensive review examines the role of sustainable aviation fuels (SAFs) in promoting a more environmentally responsible aviation industry. This study explores various types of biofuels, including hydroprocessed esters and fatty acids (HEFAs), Fischer–Tropsch (FT) fuels, alcohol-to-jet (ATJ) fuels, and oil derived from
[...] Read more.
This comprehensive review examines the role of sustainable aviation fuels (SAFs) in promoting a more environmentally responsible aviation industry. This study explores various types of biofuels, including hydroprocessed esters and fatty acids (HEFAs), Fischer–Tropsch (FT) fuels, alcohol-to-jet (ATJ) fuels, and oil derived from algae. Technological advancements in production and processing have enabled SAF to offer significant reductions in greenhouse gas emissions and other pollutants, contributing to a cleaner environment and better air quality. The review addresses the environmental, economic, and technical benefits of SAF, as well as the challenges associated with their adoption. Lifecycle analyses are used to assess the net environmental benefits of SAF, with a focus on feedstock sustainability, energy efficiency, and potential impacts on biodiversity and land use. Challenges such as economic viability, scalability, and regulatory compliance are discussed, with emphasis on the need for supportive policies and international collaboration to ensure the long-term sustainability of SAF. This study also explores current applications of SAF in commercial airlines and military settings, highlighting successful case studies and regional differences driven by policy frameworks and government incentives. By promoting technological innovation and addressing regulatory and economic barriers, SAF has the potential to play a crucial role in the aviation industry’s transition toward sustainability.
Full article
(This article belongs to the Special Issue Advanced Research in Combustion Energy: Optimization, Applications, and Analysis)
►▼
Show Figures
Figure 1
Open AccessArticle
Improved Model-Free Deadbeat Predictive Current Controller for PMSMs Based on Ultralocal Model and H∞ Norm
by
Yiming Fang and Junlei Chen
Energies 2024, 17(11), 2649; https://doi.org/10.3390/en17112649 - 30 May 2024
Abstract
This article proposes an improved model-free deadbeat predictive current control (MFCC) method for permanent magnet synchronous motors (PMSMs) based on the ultralocal model and H∞ norm. Firstly, the traditional deadbeat predictive current control (DPCC) method is introduced and a theoretical analysis is
[...] Read more.
This article proposes an improved model-free deadbeat predictive current control (MFCC) method for permanent magnet synchronous motors (PMSMs) based on the ultralocal model and H∞ norm. Firstly, the traditional deadbeat predictive current control (DPCC) method is introduced and a theoretical analysis is conducted on its sensitivity to parameters. Building upon this, the limitations of model dependence and the limited robustness of the deadbeat predictive current control method based on the extended state observer (ESO-DPCC) are theoretically analyzed. Furthermore, an improved MFCC method based on the ultralocal model is proposed, and the influence of the observer on MFCC is theoretically analyzed. This study combined the proposed method with the H∞ norm, and the optimal coefficients of the observer were tuned to enhance the robustness and dynamic performance of the current loop. Finally, the proposed algorithms were validated on a 400 W PMSM platform.
Full article
(This article belongs to the Special Issue Analysis and Design of High-Energy-Efficiency Permanent Magnet Machines)
►▼
Show Figures
Figure 1
Open AccessArticle
A Dynamic Reserve Evaluation Method for an Ultra-Deep Fractured Tight Sandstone Gas Reservoir
by
Xinxing He, Chenhui Wang, Baohua Chang, Zhenglin Cao and Haifa Tang
Energies 2024, 17(11), 2648; https://doi.org/10.3390/en17112648 - 30 May 2024
Abstract
Dynamic reserves evaluation is crucial for the development and assessment of gas reservoirs. However, ultra-deep fractured tight sandstone gas reservoirs pose unique challenges due to their abnormally high pressure, tight matrix, and complex fracture distribution. This paper proposes a simplified forward calculation method
[...] Read more.
Dynamic reserves evaluation is crucial for the development and assessment of gas reservoirs. However, ultra-deep fractured tight sandstone gas reservoirs pose unique challenges due to their abnormally high pressure, tight matrix, and complex fracture distribution. This paper proposes a simplified forward calculation method that incorporates the fracture length for the rapid estimation of dynamic reserves in fractured tight sandstone gas reservoirs. This method was based on the pressure change rate equation and considered the unique characteristics of fractured gas reservoirs. Numerical simulations were conducted to analyze the sensitivity of the proposed method. The proposed method was applied to estimate the dynamic reserves of a fractured gas reservoir, and the results closely approximate the well group method, indicating its accuracy. The main advantage of this method lies in its simplicity, allowing field engineers to perform rapid dynamic reserve evaluations.
Full article
(This article belongs to the Section H3: Fossil)
►▼
Show Figures
Figure 1
Open AccessArticle
A Multistage Physics-Informed Neural Network for Fault Detection in Regulating Valves of Nuclear Power Plants
by
Chenyang Lai, Ibrahim Ahmed, Enrico Zio, Wei Li, Yiwang Zhang, Wenqing Yao and Juan Chen
Energies 2024, 17(11), 2647; https://doi.org/10.3390/en17112647 - 30 May 2024
Abstract
In Nuclear Power Plants (NPPs), online condition monitoring and the fault detection of structures, systems and components (SSCs) can aid in guaranteeing safe operation. The use of data-driven methods for these tasks is limited by the requirement of physically consistent outcomes, particularly in
[...] Read more.
In Nuclear Power Plants (NPPs), online condition monitoring and the fault detection of structures, systems and components (SSCs) can aid in guaranteeing safe operation. The use of data-driven methods for these tasks is limited by the requirement of physically consistent outcomes, particularly in safety-critical systems. Considering the importance of regulating valves (e.g., safety relief valves and main steam isolation valves), this work proposes a multistage Physics-Informed Neural Network (PINN) for fault detection in such components. Two stages of the PINN are built by developing the process model of the regulating valve, which integrates the basic valve sizing equation into the loss function to jointly train the two stages of the PINN. In the 1st stage, a shallow Neural Network (NN) with only one hidden layer is developed to estimate the equivalent flow coefficient (a key performance indicator of regulating valves) using the displacement of the valve as input. In the 2nd stage, a Deep Neural Network (DNN) is developed to estimate the flow rate expected in normal conditions using inputs such as the estimated flow coefficient from the 1st stage, the differential pressure, and the fluid temperature. Then, the residual, i.e., the difference between the estimated and measured flow rates, is fed into a Deep Support Vector Data Description (DeepSVDD) to detect the occurrence of faults. Moreover, the deviation between the estimated flow coefficients of normal and faulty conditions is used to interpret the consistency of the detection result with physics. The proposed method is, first, applied to a simulation case implemented to emulate the operating characteristics of regulating the valves of NPPs and then validated on a real-world case study based on the DAMADICS benchmark. Compared to state-of-the-art fault detection methods, the obtained results from the proposed method show effective fault detection performance and reasonable flow coefficient estimation, thus guaranteeing the physical consistency of the detection results.
Full article
(This article belongs to the Special Issue Digitalization of Nuclear Power Plant Asset Management Using Artificial Intelligence and Machine Learning Methods)
►▼
Show Figures
Figure 1
Open AccessReview
Review and Recent Advances in Metal Compounds as Potential High-Performance Anodes for Sodium Ion Batteries
by
Inji Choi, Sion Ha and Kyeong-Ho Kim
Energies 2024, 17(11), 2646; https://doi.org/10.3390/en17112646 - 30 May 2024
Abstract
Along with great attention to eco-friendly power solutions, sodium ion batteries (SIBs) have stepped into the limelight for electrical vehicles (EVs) and grid-scale energy storage systems (ESSs). SIBs have been perceived as a bright substitute for lithium ion batteries (LIBs) due to abundance
[...] Read more.
Along with great attention to eco-friendly power solutions, sodium ion batteries (SIBs) have stepped into the limelight for electrical vehicles (EVs) and grid-scale energy storage systems (ESSs). SIBs have been perceived as a bright substitute for lithium ion batteries (LIBs) due to abundance on Earth along with the cost-effectiveness of Na resources compared to Li counterparts. Nevertheless, there are still inherent challenges to commercialize SIBs due to the relatively larger ionic radius and sluggish kinetics of Na+ ions than those of Li+ ions. Particularly, exploring novel anode materials is necessary because the conventional graphite anode in LIBs is less active in Na cells and hard carbon anodes exhibit a poor rate capability. Various metal compounds have been examined for high-performance anode materials in SIBs and they exhibit different electrochemical performances depending on their compositions. In this review, we summarize and discuss the correlation between cation and anion compositions of metal compound anodes and their structural features, energy storage mechanisms, working potentials, and electrochemical performances. On top of that, we also present current research progress and numerous strategies for achieving high energy density, power, and excellent cycle stability in anode materials.
Full article
(This article belongs to the Special Issue Advanced Battery Materials for Energy Storage)
►▼
Show Figures
Figure 1
Open AccessArticle
Sustainable Transport in the European Union: Exploring the Net-Zero Transition through Confirmatory Factor Analysis and Gaussian Graphical Modeling
by
Mirela Sichigea, Daniel Cîrciumaru, Valeriu Brabete and Cătălin Mihail Barbu
Energies 2024, 17(11), 2645; https://doi.org/10.3390/en17112645 - 30 May 2024
Abstract
The sustainability of the transport sector is targeted by various policies adopted by the European Union, and their impact must be constantly monitored in order to maximize the desired objective. This paper, through a two-stage investigation, aims to present a systemic approach of
[...] Read more.
The sustainability of the transport sector is targeted by various policies adopted by the European Union, and their impact must be constantly monitored in order to maximize the desired objective. This paper, through a two-stage investigation, aims to present a systemic approach of the sustainability dimensions in transport and to introduce an innovative technique to analyze the interdependencies between them. In the first stage, relevant indicators were selected from the Eurostat database for the content of four dimensions: economic, environmental, social and technological. The robustness of the developed dimensions was assessed and validated through a confirmatory factor analysis. In the second stage, a Gaussian graphical model was estimated as a technique integrating graphical and statistical modeling to identify complex structures of linkages between variables (as components of each dimension of sustainability). The structure of the network clearly highlights the dependence of transport on fossil fuel consumption as the main determinant of pollution in the sector (CO2 emissions). In addition, the central role of railways in decarbonizing transport is highlighted, in contrast to the limited, and isolated at one end of the network, role of electric vehicles. The findings support that affordability of this new technology plays an important role in its impact on zero-emission transition. Concentrating on the period 2013–2022, at EU27 level, the results are relevant in the context of decarbonization policies, offering useful insights both for future research and policy makers.
Full article
(This article belongs to the Section B: Energy and Environment)
►▼
Show Figures
Figure 1
Open AccessArticle
Investigation of the Near Future Solar Energy Changes Using a Regional Climate Model over Istanbul, Türkiye
by
Yusuf Duran, Elif Yavuz, Bestami Özkaya, Yüksel Yalçin, Çağatay Variş and S. Levent Kuzu
Energies 2024, 17(11), 2644; https://doi.org/10.3390/en17112644 - 30 May 2024
Abstract
This study aims to assess potential changes in radiation values at the solar power plant facility in Istanbul using the RegCM. This analysis seeks to estimate the extent of the solar radiation changes and evaluate the production capacity of solar power in Istanbul
[...] Read more.
This study aims to assess potential changes in radiation values at the solar power plant facility in Istanbul using the RegCM. This analysis seeks to estimate the extent of the solar radiation changes and evaluate the production capacity of solar power in Istanbul in the future. The research involved installing an off-grid rooftop solar energy system. Meteorological parameters (temperature, etc.) and the system’s outputs were monitored to evaluate the energy production and its relationship with these parameters. The performance of the Regional Climate Model version 5.0 (RegCMv5) in accurately representing surface solar radiation and temperature patterns was assessed by comparing it with measured monocrystalline solar panel output data. The impact of different cumulus convection schemes was examined on the sensitivity of the RegCM by analyzing surface solar radiation data over the initial three months. Long-term simulations were conducted with the representational concentration path (RCP) scenarios of 2.6, 4.5, and 8.5 spanning from 2023 to 2050 with convection schemes yielding the best results. All scenarios project a slight decrease in incoming surface radiation.
Full article
(This article belongs to the Topic Clean Energy Technologies and Assessment)
►▼
Show Figures
Figure 1
Open AccessArticle
Adaptive Quasi-Super-Twisting Sliding Mode Control for Flexible Multistate Switch
by
Wenzhong Ma, Xiao Wang, Yusheng Wang, Wenyan Zhang, Hengshuo Li and Yaheng Zhu
Energies 2024, 17(11), 2643; https://doi.org/10.3390/en17112643 - 29 May 2024
Abstract
The mathematical model of a flexible multistate switch (FMSS) exhibits nonlinear and strong coupling characteristics, whereas traditional power decoupling control makes it difficult to completely decouple the output power. The traditional proportional–integral control parameters are difficult to adjust, and their robustness and dynamic
[...] Read more.
The mathematical model of a flexible multistate switch (FMSS) exhibits nonlinear and strong coupling characteristics, whereas traditional power decoupling control makes it difficult to completely decouple the output power. The traditional proportional–integral control parameters are difficult to adjust, and their robustness and dynamic performance are poor, which affects the stability of the voltage of the power distribution network and feeder power. To address these problems, this study first converted the original system into a linear system via coordinate transformation using feedback-accurate linearization to decouple active and reactive currents. Thereafter, a super-twisting sliding mode control (ST-SMC) algorithm was introduced, and an adaptive quasi-super-twisting sliding mode control (AQST-SMC) algorithm comprising the quasi-sliding mode function and adaptive proportional term was proposed. An FMSS double closed-loop controller was designed to achieve improved vibration suppression and convergence speed. A three-port FMSS simulation model was developed using MATLAB/Simulink, and the simulation results show that the proposed control strategy enhances the robustness and dynamic performance of the system.
Full article
(This article belongs to the Special Issue Advanced Power Electronics Technology)
Journal Menu
► ▼ Journal Menu-
- Energies Home
- Aims & Scope
- Editorial Board
- Reviewer Board
- Topical Advisory Panel
- Instructions for Authors
- Special Issues
- Topics
- Sections & Collections
- Article Processing Charge
- Indexing & Archiving
- Editor’s Choice Articles
- Most Cited & Viewed
- Journal Statistics
- Journal History
- Journal Awards
- Society Collaborations
- Conferences
- Editorial Office
Journal Browser
► ▼ Journal BrowserHighly Accessed Articles
Latest Books
E-Mail Alert
News
Topics
Topic in
Energies, Materials, Processes, Solar, Sustainability
Solar Thermal Energy and Photovoltaic Systems, 2nd Volume
Topic Editors: Pedro Dinis Gaspar, Pedro Dinho da Silva, Luís C. PiresDeadline: 31 May 2024
Topic in
Applied Sciences, Electricity, Electronics, Energies, Sensors
Power System Protection
Topic Editors: Seyed Morteza Alizadeh, Akhtar KalamDeadline: 20 June 2024
Topic in
Economies, Energies, Mathematics, Sustainability
Energy Economics and Sustainable Development
Topic Editors: Cuihong Yang, Xiuting Li, Zhuoying Zhang, Xuerong LiDeadline: 30 June 2024
Topic in
Remote Sensing, Energies, Minerals, Geosciences, Geotechnics
Support Theory and Technology of Geotechnical Engineering
Topic Editors: Qi Wang, Bei Jiang, Xuezhen Wu, Hongke GaoDeadline: 20 July 2024
Conferences
Special Issues
Special Issue in
Energies
Modeling and Simulation of Floating Offshore Wind Farms
Guest Editor: M. Salman SiddiquiDeadline: 31 May 2024
Special Issue in
Energies
Governance, Legislation and Economic Policy for Green Energy Production: The EU Green Deal Framework and Horizon 2030
Guest Editors: Antonio Sánchez-Bayón, Estrella Trincado, Jesús Alberto Valero-Matas, Rafael Rávina-RipollDeadline: 19 June 2024
Special Issue in
Energies
Tidal Turbines II
Guest Editors: Sylvain Guillou, Eric L. Bibeau, Jérôme ThiebotDeadline: 30 June 2024
Special Issue in
Energies
Energy Policy and Sustainable Development: Challenges to Economic Development
Guest Editors: Rafał Nagaj, Jacek KamińskiDeadline: 11 July 2024
Topical Collections
Topical Collection in
Energies
Featured Papers in Electrical Power and Energy System
Collection Editors: Nicu Bizon, Mihai Oproescu, Philippe Poure, Rocío Pérez de Prado, Abdessattar Abdelkefi
Topical Collection in
Energies
Energy Economics and Policy in Developed Countries
Collection Editor: Almas Heshmati
Topical Collection in
Energies
Editorial Board Members’ Collection Series: Advances in Power Converters
Collection Editors: Rosa Anna Mastromauro, Luigi Piegari
Topical Collection in
Energies
Artificial Intelligence and Smart Energy
Collection Editors: Wei-Hsin Chen, Núria Agell, Zhiyong Liu, Ying-Yi Hong