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
Passive Shunted Piezoelectric Systems for Vibration Control of Wind Turbine Towers: A Feasibility Study
Energies 2024, 17(10), 2420; https://doi.org/10.3390/en17102420 - 17 May 2024
Abstract
Many countries have a variety of offshore and onshore wind turbines that face extreme aging challenges. Issues with harmful vibrations that must be minimized are addressed in this paper. A new method of wind turbine tower vibration control using piezoelectricity and shunt circuits
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Many countries have a variety of offshore and onshore wind turbines that face extreme aging challenges. Issues with harmful vibrations that must be minimized are addressed in this paper. A new method of wind turbine tower vibration control using piezoelectricity and shunt circuits is proposed in this paper. The passive vibration control method is shown to improve the tower’s structural performance under various environmental loads, like wind and seismic excitations. To examine the effectiveness of the suggested shunted piezoelectric system, a simple surrogate finite element model of a wind turbine tower is considered, and various investigations at the second eigenfrequency are carried out. An alternative way of modeling the studied structure is considered and the results demonstrate better performance. The advantages of setting up structural damping systems for decreasing tower vibrational loads and boosting their structural stability and resilience against extreme events are highlighted throughout this work.
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(This article belongs to the Special Issue Sustainable Energy Artificial Islands)
Open AccessArticle
A Stochastic Decision-Making Tool Suite for Distributed Energy Resources Integration in Energy Markets
by
Sergio Cantillo-Luna, Ricardo Moreno-Chuquen, David Celeita and George J. Anders
Energies 2024, 17(10), 2419; https://doi.org/10.3390/en17102419 - 17 May 2024
Abstract
Energy markets are crucial for integrating Distributed Energy Resources (DER) into modern power grids. However, this integration presents challenges due to the inherent variability and decentralized nature of DERs, as well as poorly adapted regulatory environments. This paper proposes a medium-term decision-making approach
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Energy markets are crucial for integrating Distributed Energy Resources (DER) into modern power grids. However, this integration presents challenges due to the inherent variability and decentralized nature of DERs, as well as poorly adapted regulatory environments. This paper proposes a medium-term decision-making approach based on a comprehensive suite of computational tools for integrating DERs into Colombian energy markets. The proposed framework consists of modular tools that are aligned with the operation of a Commercial Virtual Power Plant (CVPP). The tools aim to optimize participation in bilateral contracts and short-term energy markets. They use forecasting, uncertainty management, and decision-making modules to create an optimal portfolio of DER assets. The suite’s effectiveness and applicability are demonstrated and analyzed through its implementation with heterogeneous DER assets across various operational scenarios.
Full article
(This article belongs to the Section C: Energy Economics and Policy)
Open AccessArticle
Lithium-Ion Batteries (LIBs) Immersed in Fire Prevention Material for Fire Safety and Heat Management
by
Junho Bae, Yunseok Choi and Youngsik Kim
Energies 2024, 17(10), 2418; https://doi.org/10.3390/en17102418 - 17 May 2024
Abstract
Lithium-ion batteries (LIBs) have emerged as the most commercialized rechargeable battery technology. However, their inherent property, called thermal runaway, poses a high risk of fire. This article introduces the “Battery Immersed in Fire Prevention Material (BIF)”, the immersion-type battery in which all of
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Lithium-ion batteries (LIBs) have emerged as the most commercialized rechargeable battery technology. However, their inherent property, called thermal runaway, poses a high risk of fire. This article introduces the “Battery Immersed in Fire Prevention Material (BIF)”, the immersion-type battery in which all of the LIB cells are surrounded by a liquid agent. This structure and the agent enable active battery fire suppression under abusive conditions while facilitating improved thermal management during normal operation. Abuse tests involving a battery revealed that the LIB module experienced fire, explosions, and burnouts with the target cell reaching temperatures of 1405 °C and the side reaching 796 °C. Conversely, the BIF module exhibited a complete lack of fire propagation, with temperatures lower than those of LIBs, particularly 285 and 17 °C, respectively. Under normal operating conditions, the BIF module exhibited an average temperature rise ~8.6 times lower than that of a normal LIB. Furthermore, it reduced the uneven thermal deviation between the cells by ~5.3 times more than LIB. This study provides a detailed exploration of the BIF and covers everything from components to practical applications. With further improvements, this technology can significantly enhance fire safety and prevent the thermal degradation of batteries in the real world.
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(This article belongs to the Special Issue Advances in Battery Energy Storage Systems)
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An Overview of the Thermochemical Valorization of Sewage Sludge: Principles and Current Challenges
by
Bruna Rijo, Catarina Nobre, Paulo Brito and Paulo Ferreira
Energies 2024, 17(10), 2417; https://doi.org/10.3390/en17102417 - 17 May 2024
Abstract
With the increase in the world population and economic activity, the production of sewage sludge has grown, and its management has become an environmental problem. The most traditional method of managing sewage sludge is to dispose of it in landfills and on farmland.
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With the increase in the world population and economic activity, the production of sewage sludge has grown, and its management has become an environmental problem. The most traditional method of managing sewage sludge is to dispose of it in landfills and on farmland. One way to valorize sewage sludge is to use thermochemical conversion processes to produce added-value products such as biochar, biofuels, and renewable gases. However, due to the high moisture content, thermochemical conversion using processes such as pyrolysis and traditional gasification involves multiple pre-treatment processes such as material drying. Hydrothermal thermochemical processes usually require high pressures, which pose many challenges to their application on a large scale. In this work, the advantages and disadvantages of the different existing thermochemical processes for the recovery of sewage sludge were analyzed, as well as the resulting industrial and environmental challenges. A SWOT analysis was carried out to assess the different thermochemical processes in terms of technical feasibility, economic viability, and broader market considerations.
Full article
(This article belongs to the Special Issue Sustainable Technologies for Decarbonising the Energy Sector)
Open AccessArticle
Numerical Investigation of Rotor and Stator Matching Mode on the Complex Flow Field and Pressure Pulsation of a Vaned Centrifugal Pump
by
Leilei Du, Fankun Zheng, Bo Gao, Mona Gad, Delin Li and Ning Zhang
Energies 2024, 17(10), 2416; https://doi.org/10.3390/en17102416 - 17 May 2024
Abstract
The match of rotor and stator blades significantly affects the flow field structure and flow-induced pressure pulsation characteristics inside the pump. In order to study the effects of the rotor and stator matching mode on the complex flow field and pressure pulsation of
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The match of rotor and stator blades significantly affects the flow field structure and flow-induced pressure pulsation characteristics inside the pump. In order to study the effects of the rotor and stator matching mode on the complex flow field and pressure pulsation of a centrifugal pump with a vaned diffuser, this paper designs three different vaned diffusers (DY5, DY8 and DY9) and uses the DDES (Delayed Detached Eddy Simulation) numerical method combined with structured grids to simulate the unsteady flow phenomena of the model pump under rated conditions. The results show that, under different rotor and stator matching modes, the pressure pulsation spectrum is dominated by the blade passing frequency and its harmonics. The matching mode of the rotor and stator significantly affects the time–frequency domain characteristics of the pressure pulsation inside the pump, and it is observed that the pressure pulsation energy of vaned diffusers with more blades is significantly smaller than that of fewer-blade vaned diffusers in comparison to the energy of the pressure pulsation at the blade passing frequency and within the 10–1500 Hz frequency band. Combined with the distribution characteristics of the complex flow field inside the pump, it can be found that increasing the number of vaned diffuser blades can reduce the energy of flow-induced pressure pulsation, improve the distribution of high-energy vortices in the interaction zone and stabilize the flow inside the centrifugal pump effectively.
Full article
(This article belongs to the Section F: Electrical Engineering)
Open AccessArticle
Nanofluidic Study of Multiscale Phase Transitions and Wax Precipitation in Shale Oil Reservoirs
by
Zhiyong Lu, Yunqiang Wan, Lilong Xu, Dongliang Fang, Hua Wu and Junjie Zhong
Energies 2024, 17(10), 2415; https://doi.org/10.3390/en17102415 - 17 May 2024
Abstract
During hydraulic fracturing of waxy shale oil reservoirs, the presence of fracturing fluid can influence the phase behavior of the fluid within the reservoir, and heat exchange between the fluids causes wax precipitation that impacts reservoir development. To investigate multiscale fluid phase transition
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During hydraulic fracturing of waxy shale oil reservoirs, the presence of fracturing fluid can influence the phase behavior of the fluid within the reservoir, and heat exchange between the fluids causes wax precipitation that impacts reservoir development. To investigate multiscale fluid phase transition and microscale flow impacted by fracturing fluid injection, this study conducted no-water phase behavior experiments, water injection wax precipitation experiments, and water-condition phase behavior experiments using a nanofluidic chip model. The results show that in the no-water phase experiment, the gasification occurred first in the large cracks, while the matrix throat was the last, and the bubble point pressure difference between the two was 12.1 MPa. The wax precipitation phenomena during fracturing fluid injection can be divided into granular wax in cracks, flake wax in cracks, and wax precipitation in the matrix throat, and the wax mainly accumulated in the microcracks and remained in the form of particles. Compared with the no-water conditions, the large cracks and matrix throat bubble point in the water conditions decreased by 6.1 MPa and 3.5 MPa, respectively, and the presence of the water phase reduced the material occupancy ratio at each pore scale. For the smallest matrix throat, the final gas occupancy ratio under the water conditions decreased from 32% to 24% in the experiment without water. This study provides valuable insight into reservoir fracture modification and guidance for the efficient development of similar reservoirs.
Full article
(This article belongs to the Section H: Geo-Energy)
Open AccessArticle
Large-Eddy vs. Reynolds-Averaged Navier–Stokes Simulations of Flow and Heat Transfer in a U-Duct with Unsteady Flow Separation
by
Kenny S. Hu and Tom I-P. Shih
Energies 2024, 17(10), 2414; https://doi.org/10.3390/en17102414 - 17 May 2024
Abstract
Large-eddy simulation (LES) and Reynolds-Averaged Navier–Stokes (RANS) equations were used to study incompressible flow and heat transfer in a U-duct with a high-aspect-ratio trapezoidal cross section. For the LES, the WALE subgrid-scale model was employed, and its inflow boundary condition was provided by
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Large-eddy simulation (LES) and Reynolds-Averaged Navier–Stokes (RANS) equations were used to study incompressible flow and heat transfer in a U-duct with a high-aspect-ratio trapezoidal cross section. For the LES, the WALE subgrid-scale model was employed, and its inflow boundary condition was provided by a concurrent LES of incompressible fully-developed flow in a straight duct with the same cross section and flow conditions as the U-duct. LES results are presented for turbulent kinetic energy, Reynolds stresses, pressure–strain rate, turbulent diffusion, turbulent transport, and velocity–temperature correlations, with a focus on how they are affected by the U-turn region of the U-duct. The LES results were also used to assess three commonly used RANS models: the realizable k-ε with the two-layer model in the near-wall region, the two-equation shear-stress transport model, and the seven-equation stress-omega Reynolds stress model. Results obtained show steady and unsteady RANS to incorrectly predict the effects of unsteady flow separation. The results obtained also identified the terms in the RANS models that need to be modified and suggested how turbulent diffusion should be modeled when there is unsteady flow separation.
Full article
(This article belongs to the Special Issue High-Performance Numerical Simulation in Heat Transfer)
Open AccessArticle
Enhancing a Deep Learning Model for the Steam Reforming Process Using Data Augmentation Techniques
by
Zofia Pizoń, Shinji Kimijima and Grzegorz Brus
Energies 2024, 17(10), 2413; https://doi.org/10.3390/en17102413 - 17 May 2024
Abstract
Methane steam reforming is the foremost method for hydrogen production, and it has been studied through experiments and diverse computational models to enhance its energy efficiency. This study focuses on employing an artificial neural network as a model of the methane steam reforming
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Methane steam reforming is the foremost method for hydrogen production, and it has been studied through experiments and diverse computational models to enhance its energy efficiency. This study focuses on employing an artificial neural network as a model of the methane steam reforming process. The proposed data-driven model predicts the output mixture’s composition based on reactor operating conditions, such as the temperature, steam-to-methane ratio, nitrogen-to-methane ratio, methane flow, and nickel catalyst mass. The network, a feedforward type, underwent training with a comprehensive dataset augmentation strategy that augments the primary experimental dataset through interpolation and theoretical simulations of the process, ensuring a robust model training phase. Additionally, it introduces weights to evaluate the relative significance of different data categories (experimental, interpolated, and theoretical) within the dataset. The optimal artificial neural network architecture was determined by evaluating various configurations, with the aim of minimizing the mean squared error (0.00022) and maximizing the Pearson correlation coefficient (0.97) and Spearman correlation coefficient (1.00).
Full article
(This article belongs to the Special Issue Hydrogen-Based Energy Systems for Sustainable Transportation)
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Hierarchically Distributed Charge Control of Plug-In Hybrid Electric Vehicles in a Future Smart Grid
by
Hanyun Zhou, Wei Li and Jiekai Shi
Energies 2024, 17(10), 2412; https://doi.org/10.3390/en17102412 - 17 May 2024
Abstract
Plug-in hybrid electric vehicles (PHEVs) are becoming increasingly widespread due to their environmental benefits. However, PHEV penetration can overload distribution systems and increase operational costs. It is a major challenge to find an economically optimal solution under the condition of flattening load demand
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Plug-in hybrid electric vehicles (PHEVs) are becoming increasingly widespread due to their environmental benefits. However, PHEV penetration can overload distribution systems and increase operational costs. It is a major challenge to find an economically optimal solution under the condition of flattening load demand for systems. To this end, we formulate this problem as a two-layer optimization problem, and propose a hierarchical algorithm to solve it. For the upper layer, we flatten the load demand curve by using the water-filling principle. For the lower layer, we minimize the total cost for all consumers through a consensus-like iterative method in a distributed manner. Technical constraints caused by consumer demand and power limitations are both taken into account. In addition, a moving horizon approach is used to handle the random arrival of PHEVs and the inaccuracy of the forecast base demand. This paper focuses on distributed solutions under a time-varying switching topology so that all PHEV chargers conduct local computation and merely communicate with their neighbors, which is substantially different from the existing works. The advantages of our algorithm include a reduction in computational burden and high adaptability, which clearly has its own significance for the future smart grid. Finally, we demonstrate the advantages of the proposed algorithm in both theory and simulation.
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(This article belongs to the Section A1: Smart Grids and Microgrids)
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National Environmental Taxes and Industrial Waste in Countries across Europe
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Eirini Stergiou, Nikos Rigas, Giancarlo Ferrara, Eleni Mantzari and Konstantinos Kounetas
Energies 2024, 17(10), 2411; https://doi.org/10.3390/en17102411 - 17 May 2024
Abstract
The use of economic instruments within environmental policy has become a challenging topic for policymakers, governments and scholars. Environmental taxes have emerged as a prevailing preference in developed countries to promote sustainability. Recently, a particular focus has been given to waste generation and
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The use of economic instruments within environmental policy has become a challenging topic for policymakers, governments and scholars. Environmental taxes have emerged as a prevailing preference in developed countries to promote sustainability. Recently, a particular focus has been given to waste generation and disposal, shifting the attention from greenhouse gases to another important source of environmental pollution. This paper investigates the effect of national environmental taxes and policies on industrial waste. A fixed effects model is used for 34 countries across Europe from 2004 to 2022. The results suggest that environmental taxes and energy policies reduce industrial (hazardous and non-hazardous) waste. However, environmental tax reforms should take into consideration the deterioration in environmental quality, the increase in economic costs and undesirable social consequences.
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(This article belongs to the Special Issue Sustainable Energy Economics and Prospects Research)
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Improved Design and Economic Estimation of Cold-End Systems for Inland Nuclear Power Plants
by
Wenjie Zhang, Yushan Li, Peiqi Liu and Huimin Wei
Energies 2024, 17(10), 2410; https://doi.org/10.3390/en17102410 - 17 May 2024
Abstract
Reserve sites for coastal nuclear power plants are gradually being depleted, prompting a shift towards the development of inland nuclear power stations. A new cooling system based on the integration of multiple cooling sources using a hybrid dry–wet cycle is proposed to achieve
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Reserve sites for coastal nuclear power plants are gradually being depleted, prompting a shift towards the development of inland nuclear power stations. A new cooling system based on the integration of multiple cooling sources using a hybrid dry–wet cycle is proposed to achieve a balance between energy and water consumption for inland nuclear power stations. Comparative studies among all the available cooling systems were further conducted to analyze the cooling performance and economic viability. The case study results indicate that, in comparison to relative humidity, the cooling performance and circulating water consumption of cooling systems are more susceptible to changes in dry-bulb temperature. In arid and water-scarce regions, a Combined Natural Draft Hybrid Cooling System generally exhibits a monthly average circulating water consumption rate that is more than 270 kg/s lower than that of the natural draft wet cooling system, with an average monthly back pressure reduction of 0.11 kPa. When the dry-bulb temperature exceeds 13 °C, the net profit of wet cooling surpasses that of hybrid cooling. However, this scenario undergoes a reversal as the dry-bulb temperature decreases and local water prices rise. It is emphasized that hybrid cooling demonstrates minimal impact when subjected to changes in environmental conditions, offering extensive regional applicability.
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(This article belongs to the Section B4: Nuclear Energy)
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Research on Quantitative Diagnosis of Dendrites Based on Titration Gas Chromatography Technology
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Kai Yang, Hongchang Cai, Suran Li, Yu Wang, Xue Zhang, Zhenxuan Wu, Yilin Lai, Minella Bezha, Klara Bezha, Naoto Nagaoka, Yuejiu Zheng and Xuning Feng
Energies 2024, 17(10), 2409; https://doi.org/10.3390/en17102409 - 17 May 2024
Abstract
Lithium plating can cause capacity fade and thermal runaway safety issues in lithium-ion batteries. Therefore, accurately detecting the amount of lithium plating on the surface of the battery’s negative electrode is crucial for battery safety. This is especially crucial in high-energy-density applications such
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Lithium plating can cause capacity fade and thermal runaway safety issues in lithium-ion batteries. Therefore, accurately detecting the amount of lithium plating on the surface of the battery’s negative electrode is crucial for battery safety. This is especially crucial in high-energy-density applications such as battery energy storage systems or in electric vehicles (EVs). Early detection of lithium plating is crucial for evaluation of reliability and longevity. It also serves as a method for early diagnostics in practical industrial applications or infrastructure, such as EV transportation. This can enhance its impact on customers. This study validates the effectiveness of titration gas chromatography (TGC) technology in quantitatively detecting lithium plating on graphite negative electrodes in lithium-ion batteries. The results show that it can detect a minimum of 2.4 μmol of metallic lithium. Compared with the heating direct current resistance and reference electrode methods, which can be used to perform only qualitative dendrite detection, TGC has a wider range of detection. Compared with the nuclear magnetic resonance (NMR) method with higher quantitative detection accuracy, the maximum difference between the detection results of the two methods was only 7.2%, but the TGC method had lower cost and higher implementation convenience. In summary, among various dendrite detection methods, the TGC method can not only realize the effective quantitative detection of lithium plating, but also comprehensively consider its detection range, implementation convenience, cost, and detection accuracy, indicating that it is suitable for engineering applications and has the prospect of realizing large-scale quantitative detection of lithium plating in lithium-ion batteries.
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(This article belongs to the Special Issue Advances in Battery Technologies for Electric Vehicles)
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Infrastructure Diagnosed by Solar Power Supply in an Intelligent Diagnostic System in Five-Valued Logic
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Stanisław Duer, Marek Woźniak, Jacek Paś, Marek Stawowy, Krzysztof Rokosz, Dariusz Bernatowicz, Radosław Duer and Atif Iqbal
Energies 2024, 17(10), 2408; https://doi.org/10.3390/en17102408 - 17 May 2024
Abstract
This article discusses the issue of diagnosing low-power solar power plants using the five-valued (5VL) state evaluation {4, 3, 2, 1, 0}. We address in depth how the 5VL diagnostics built upon 2VL, 3VL, and 4VL—two-valued diagnostics, three-valued logistics, and four-valued diagnostics. Logic
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This article discusses the issue of diagnosing low-power solar power plants using the five-valued (5VL) state evaluation {4, 3, 2, 1, 0}. We address in depth how the 5VL diagnostics built upon 2VL, 3VL, and 4VL—two-valued diagnostics, three-valued logistics, and four-valued diagnostics. Logic (5VL) assigns five state values to the range of signal value changes, and these states are completely operational ({4}), incomplete ({3}), critical efficiency ({2}), and pre-fault efficiency ({1}). For the identical ranges of diagnostic signal values, all three of the applied state valence logics interpret failure as changes outside of their permitted ranges. Diagnostic procedures made use of an AI-based DIAG 2 system. This article’s goal is to provide a comprehensive overview of the DIAG 2 intelligent diagnostic system, including its architecture, algorithm, and inference rules. Diagnosis with the DIAG 2 system is based on a well-established technique for comparing diagnostic signal vectors with reference signal vectors. A differential vector metric is born out of this examination of vectors. The input cells of the neural network implement the challenge of signal analysis and comparison. It is then possible to classify the object components’ states in the neural network’s output cells. Based on the condition of the object’s constituent parts, this approach can signal whether those parts are working, broken, or urgently require replacement.
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(This article belongs to the Special Issue Intelligent Systems Supporting the Use of Energy Device and Other Complex Technical Objects, 2nd Edition)
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Open AccessCorrection
Correction: Matchim Kamden et al. A Comprehensive Study on DES Pretreatment Application to Microalgae for Enhanced Lipid Recovery Suitable for Biodiesel Production: Combined Experimental and Theoretical Investigations. Energies 2023, 16, 3806
by
Michele Corneille Matchim Kamdem, Aymard Didier Tamafo Fouegue and Nanjun Lai
Energies 2024, 17(10), 2407; https://doi.org/10.3390/en17102407 - 17 May 2024
Abstract
The authors wish to make the following correction to this paper [...]
Full article
(This article belongs to the Special Issue Biomass Conversion Technologies III)
Open AccessArticle
A Novel Adjoint-Based Reduced-Order Model for Depletion Calculations in Nuclear Reactor Physics
by
Thibault Sauzedde, Pascal Archier and Frédéric Nguyen
Energies 2024, 17(10), 2406; https://doi.org/10.3390/en17102406 - 16 May 2024
Abstract
The licensing of new reactors implies the use of verified and validated neutronic codes. Numerical validation can rely on sensitivity and uncertainty studies, but they require repeated execution of time-consuming neutron flux and depletion calculations. The computational costs can be reduced by using
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The licensing of new reactors implies the use of verified and validated neutronic codes. Numerical validation can rely on sensitivity and uncertainty studies, but they require repeated execution of time-consuming neutron flux and depletion calculations. The computational costs can be reduced by using perturbation theories. However, the uncoupled Depletion Perturbation Theory is restricted to single integral values such as nuclide density. Relying on reduced-basis approaches, which reconstruct all nuclide densities at once, is one way to get around this restriction. Furthermore, the adjoint-based reduced-order model uses the direct and adjoint equations for projection. For diffusion or transport calculations, the Exact-to-Precision Generalized Perturbation Theory was developed. Still, no models for depletion calculations are readily available. Therefore, this paper describes a novel adjoint-based reduced-order model for the Bateman Equation. It uses a range-finding algorithm to create the basis and the uncoupled Depletion Perturbation Theory for the reconstruction of the first order replaced by with a first order formulation. Our paper shows that for several perturbed cases, the depletion reduced-order model successfully reconstructs the nuclide densities. As a result, this serves as a proof of concept for our adjoint-based reduced-order model, which can perform sensitivity and uncertainty burn-up analysis in a shorter time.
Full article
(This article belongs to the Special Issue Advanced Multi-Physics Modeling, Simulation, and Optimization for Nuclear Technology)
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Spray Characterization of Direct Hydrogen Injection as a Green Fuel with Lower Emissions
by
Raul Payri, Ricardo Novella, Khodor I. Nasser and Oscar Bori-Fabra
Energies 2024, 17(10), 2405; https://doi.org/10.3390/en17102405 - 16 May 2024
Abstract
A viable green energy source for heavy industries and transportation is hydrogen. The internal combustion engine (ICE), when powered by hydrogen, offers an economical and adaptable way to quickly decarbonize the transportation industry. In general, two techniques are used to inject hydrogen into
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A viable green energy source for heavy industries and transportation is hydrogen. The internal combustion engine (ICE), when powered by hydrogen, offers an economical and adaptable way to quickly decarbonize the transportation industry. In general, two techniques are used to inject hydrogen into the ICE combustion chamber: port injection and direct injection. The present work examined direct injection technology, highlighting the need to understand and manage hydrogen mixing within an ICE’s combustion chamber. Before combusting hydrogen, it is critical to study its propagation and mixture behavior just immediately before burning. For this purpose, the DI-CHG.2 direct injector model by BorgWarner was used. This injector operated at 35 barG and 20 barG as maximum and minimum upstream pressures, respectively; a 5.8 g/s flow rate; and a maximum tip nozzle temperature of 250 °C. Experiments were performed using a high-pressure and high-temperature visualization vessel available at our facility. The combustion mixture prior to burning (spray) was visually controlled by the single-pass high-speed Schlieren technique. Images were used to study the spray penetration (S) and spray volume (V). Several parameters were considered to perform the experiments, such as the injection pressure (Pinj), chamber temperature (Tch), and the injection energizing time (Tinj). With pressure ratio and injection time being the parameters commonly used in jet characterization, the addition of temperature formed a more comprehensive group of parameters that should generally aid in the characterization of this type of gas jets as well as the understanding of the combined effect of the rate of injection on the overall outcome. It was observed that the increase in injection pressure (Pinj) increased the spray penetration depth and its calculated volume, as well as the amount of mass injected inside the chamber according to the ROI results; furthermore, it was also observed that with a pressure difference of 20 bar (the minimum required for the proper functioning of the injector used), cyclic variability increased. The variation in temperature inside the chamber had less of an impact on the spray shape and its penetration; instead, it determined the velocity at which the spray reached its maximum length. In addition, the injection energizing time had no effect on the spray penetration.
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(This article belongs to the Section A5: Hydrogen Energy)
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Standby Power Reduction of Home Appliance by the i-HEMS System Using Supervised Learning Techniques
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Beungyong Park, Suh-hyun Kwon and Byoungchull Oh
Energies 2024, 17(10), 2404; https://doi.org/10.3390/en17102404 - 16 May 2024
Abstract
Electricity consumption in homes is on the rise due to the increasing prevalence of home appliances and longer hours spent indoors. Home energy management systems (HEMSs) are emerging as a solution to reduce electricity consumption and efficiently manage power usage at home. In
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Electricity consumption in homes is on the rise due to the increasing prevalence of home appliances and longer hours spent indoors. Home energy management systems (HEMSs) are emerging as a solution to reduce electricity consumption and efficiently manage power usage at home. In the past, numerous studies have been conducted on the management of electricity production and consumption through solar power. However, there are limited human-centered studies focusing on the user’s lifestyle. In this study, we propose an Intelligent Home Energy Management System (i-HEMS) and evaluate its energy-saving effectiveness through a demonstration in a standard house in Korea. The system utilizes an IoT environment, PID sensing, and behavioral pattern algorithms. We developed algorithms based on power usage monitoring data of home appliances and human body detection. These algorithms are used as the primary scheduling algorithm and a secondary algorithm for backup purposes. We explored the deep connection between power usage, environmental sensor data, and input schedule data based on Long Short-Term Memory network (LSTM) and developed an occupancy prediction algorithm. We analyzed the use of common home appliances (TV, computer, water purifier, microwave, washing machine, etc.) in a standard house and the power consumption reduction by the i-HEMS system. Through a total of six days of empirical experiments, before implementing i-HEMS, home appliances consumed 13,062 Wh. With i-HEMS, the total consumption was reduced to 10,434 Wh (a 20% reduction), with 9060 Wh attributed to home appliances and 1374 Wh to i-HEMS operation.
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(This article belongs to the Section G: Energy and Buildings)
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New Advances in Materials, Applications, and Design Optimization of Thermocline Heat Storage: Comprehensive Review
by
Yunshen Zhang, Yun Guo, Jiaao Zhu, Weijian Yuan and Feng Zhao
Energies 2024, 17(10), 2403; https://doi.org/10.3390/en17102403 - 16 May 2024
Abstract
To achieve sustainable development goals and meet the demand for clean and efficient energy utilization, it is imperative to advance the penetration of renewable energy in various sectors. Energy storage systems can mitigate the intermittent issues of renewable energy and enhance the efficiency
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To achieve sustainable development goals and meet the demand for clean and efficient energy utilization, it is imperative to advance the penetration of renewable energy in various sectors. Energy storage systems can mitigate the intermittent issues of renewable energy and enhance the efficiency and economic viability of existing energy facilities. Among various energy storage technologies, thermocline heat storage (THS) has garnered widespread attention from researchers due to its stability and economic advantages. Currently, there are only a few review articles focusing on THS, and there is a gap in the literature regarding the optimization design of THS systems. Therefore, this paper provides a comprehensive review of the recent research progress in THS, elucidating its principles, thermal storage materials, applications, and optimization designs. The novelty of this work lies in the detailed classification and analysis of various optimization designs for THS, including tank shape, aspect ratio, inlet/outlet configuration, thermal energy storage materials arrangement, operating strategies, and numerical model optimization approaches. The limitations of existing research are also identified, and future perspectives are proposed, aiming to provide recommendations for THS research and contribute to the development and promotion of THS technology.
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(This article belongs to the Topic Energy Storage and Conversion: From Materials to Technologies)
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Open AccessArticle
Analysis of the Flow Behavior and Pressure Fluctuation of a Pump Turbine with Splitter Blades in Part-Load Pump Mode
by
Wei Xiao, Shaocheng Ren, Liu Chen, Bin Yan, Yilin Zhu and Yexiang Xiao
Energies 2024, 17(10), 2402; https://doi.org/10.3390/en17102402 - 16 May 2024
Abstract
The internal flow of a pump turbine is unstable in part-load pump mode for small guide-vane openings, and the strong vibration caused by pressure pulsation is related to the safe and stable operation of the unit. A pump turbine with a six-splitter-blade runner
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The internal flow of a pump turbine is unstable in part-load pump mode for small guide-vane openings, and the strong vibration caused by pressure pulsation is related to the safe and stable operation of the unit. A pump turbine with a six-splitter-blade runner was chosen for unsteady simulation analyses. A standard k-epsilon turbulence model was adopted to study the unsteady flow and pressure pulsation in part-load pump mode. The predicted results show that the flow in the draft tube and the runner with splitter blades was relatively stable and the flow of the blade-to-blade channel was symmetrical. When the inlet and outlet velocity distribution of the vanes was not uniform, a vortex began to form in the stay-vane domain. The reason for this vortex formation is explained, and it is pointed out that the existence of the vortex and backflow leads to uneven velocity distribution. The unsteady calculation results showed that the pressure-pulsation peak-to-peak amplitudes in the vaneless area and guide vanes were much higher than those of other monitor points because of rotor–stator interference between the rotating runner and the vanes. In addition, the pulsation characteristics of the monitor points at different circumferential positions in the vaneless region were quite different. In the vaneless area, the velocity gradient along the circumferential direction was very large, and there was a phenomenon of backflow. Also, the pressure pulsation was 0.2 times that of the runner rotational frequency, and the blade-passing frequency was a third-order frequency. At the outlet of the guide vane, the pressure pulsation was mainly of a low frequency with a complex vortex flow. Finally, the pressure pulsation began to decrease rapidly in the stay-vane region.
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(This article belongs to the Special Issue Recent Advances in Hydro-Mechanical Turbines: Powering the Future)
Open AccessArticle
An Adaptive Virtual Inertial Control Strategy for DC Distribution Networks
by
Junhua Xu, Weixun Liu and Guopeng He
Energies 2024, 17(10), 2401; https://doi.org/10.3390/en17102401 - 16 May 2024
Abstract
The DC distribution network is a low-inertia system, which is very sensitive to load disturbance, system failure, and other factors. By adding virtual capacitance to the converter connected to the power supply, the virtual inertia of the DC power grid can be improved.
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The DC distribution network is a low-inertia system, which is very sensitive to load disturbance, system failure, and other factors. By adding virtual capacitance to the converter connected to the power supply, the virtual inertia of the DC power grid can be improved. Firstly, this paper proposes a strategy for adjusting virtual capacitance based on the voltage change rate to achieve adaptive control of virtual inertia, which enables the converter to quickly absorb or release energy during power fluctuations. Secondly, the adaptivity of the strategy is improved and the main control parameters in the proposed control method are qualitatively analyzed. Finally, the four-terminal photovoltaic storage DC distribution network system is constructed. Through Simulink, the adaptive virtual inertia control is incorporated on the battery side to simulate and validate the effectiveness of the strategy and the rationality of parameter analysis. The results show that this method can provide flexible and adjustable inertia support for DC grids and improve the voltage stability of DC grids.
Full article
(This article belongs to the Section F: Electrical Engineering)
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