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
Research on Influencing Factors and Wind Deflection Warning of Transmission Lines Based on Meteorological Prediction
Energies 2024, 17(11), 2612; https://doi.org/10.3390/en17112612 - 28 May 2024
Abstract
Transmission lines are affected by external environmental factors such as strong winds and ice cover. In recent years, extreme weather events have increased, leading to recurrent disturbances in transmission lines because of wind deflection. These incidents have resulted in significant financial losses and
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Transmission lines are affected by external environmental factors such as strong winds and ice cover. In recent years, extreme weather events have increased, leading to recurrent disturbances in transmission lines because of wind deflection. These incidents have resulted in significant financial losses and have disrupted regular industrial and domestic activities. In this paper, the ANSYS Workbench 2020 R2 finite element analysis platform was used to establish a transmission line-hanging insulator string system model. Calculations on transmission lines were conducted considering variations in different stall spacing, height differences, wind speed, and the wind attack angle. The impact of these diverse factors on the wind deflection of insulators was scrutinized, leading to the derivation of patterns describing how the wind deflection angle shifts in response to changes in stall spacing, height differences, wind speed, and the wind attack angle. Based on the generalized linear regression network and particle swarm improved support vector machine algorithm, a meteorological prediction-based early warning method for wind deflection of transmission lines was proposed, a transmission line wind deflection early warning model was established, and the practical effect of the model was evaluated. The outcomes of this study provide crucial data for the formulation and development of ultra-high voltage (UHV) and extra-high voltage (EHV) transmission networks. Furthermore, they can contribute to the advanced detection of wind deflection issues.
Full article
(This article belongs to the Section F: Electrical Engineering)
Open AccessArticle
Lignocellulosic Residues from Fruit Trees: Availability, Characterization, and Energetic Potential Valorization
by
Gianluca Cavalaglio, Giacomo Fabbrizi, Filippo Cardelli, Leonardo Lorenzi, Mariarosaria Angrisano and Andrea Nicolini
Energies 2024, 17(11), 2611; https://doi.org/10.3390/en17112611 - 28 May 2024
Abstract
Reducing the carbon footprint of energy production is one of the most pressing challenges facing humanity today. Lignocellulosic biomass residues from fruit production industries show promise as a viable energy source. This paper presents a study of the Italian context concerning the utilization
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Reducing the carbon footprint of energy production is one of the most pressing challenges facing humanity today. Lignocellulosic biomass residues from fruit production industries show promise as a viable energy source. This paper presents a study of the Italian context concerning the utilization of orchard lignocellulosic residues for energy production as electricity or bioethanol. The potential of various orchard residues was assessed through chemical and physical analyses, and an equivalent electrical energy of about 6441.62 GWh or an amount of 0.48 Mt/y of bioethanol was obtained based on the average annual dry residue mass availability of about 3.04 Mt/y. These data represent 9.30% of the national electrical energy production from renewable sources, as well as 6.21% of the Italian demand for gasoline in 2022. Electricity generation from these residues has shown its potential as a reliable and sustainable baseload power source, as well as a source of renewable transportation fuel. The studied process could be a valuable reference to expand these concepts on a global scale to achieve a greener and more sustainable energy future.
Full article
(This article belongs to the Special Issue Sustainable Biomass Energy Production and Utilization)
Open AccessArticle
First Successful Wireline Stress Testing in a Gas Hydrate Reservoir in the Hyuganada Sea, Japan
by
Satoshi Ohtsuki, Bei Gao, Takanao Yoshii, Yuki Maehara, Daigoro Watanabe, Takayuki Kanno and Zhaoya Fan
Energies 2024, 17(11), 2610; https://doi.org/10.3390/en17112610 - 28 May 2024
Abstract
This study presents a stress testing operation conducted using a wireline formation tester in a newly discovered gas hydrate prospect located offshore in Japan. The campaign, which spanned from December 2021 to January 2022, involved drilling a well using logging-while-drilling technology. Subsequently, wireline
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This study presents a stress testing operation conducted using a wireline formation tester in a newly discovered gas hydrate prospect located offshore in Japan. The campaign, which spanned from December 2021 to January 2022, involved drilling a well using logging-while-drilling technology. Subsequently, wireline formation testing and stress testing were successfully conducted at three different depths within a gas hydrate-concentrated zone. The testing was accomplished in a single riserless descent, with the primary goal of obtaining crucial data such as mobility, formation pressure, and fracture gradient for one of the prospects. This operation marked the first stress testing job performed with dual packers in an open water and deepwater environment specifically for gas hydrate reservoirs. The study also provides a comprehensive interpretation of the data gathered during the operation. Moreover, it evaluates various properties such as formation mobility, formation pressure, initial breakdown pressure, closure pressure, fracture propagation pressure, and instantaneous shut-in pressure.
Full article
(This article belongs to the Special Issue Natural Gas Hydrates, Selected Papers from the 10th International Conference on Gas Hydrates)
Open AccessArticle
Power System State Estimation Based on Fusion of PMU and SCADA Data
by
Jiaming Zhu, Wengen Gao, Yunfei Li, Xinxin Guo, Guoqing Zhang and Wanjun Sun
Energies 2024, 17(11), 2609; https://doi.org/10.3390/en17112609 - 28 May 2024
Abstract
This paper introduces a novel hybrid filtering algorithm that leverages the advantages of Phasor Measurement Units (PMU) to address state estimation challenges in power systems. The primary objective is to integrate the benefits of PMU measurements into the design of traditional power system
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This paper introduces a novel hybrid filtering algorithm that leverages the advantages of Phasor Measurement Units (PMU) to address state estimation challenges in power systems. The primary objective is to integrate the benefits of PMU measurements into the design of traditional power system dynamic estimators. It is noteworthy that PMUs and Supervisory Control and Data Acquisition (SCADA) systems typically operate at different sampling rates in power system estimation, necessitating synchronization during the filtering process. To address this issue, the paper employs a predictive interpolation method for SCADA measurements within the framework of the Extended Kalman Filter (EKF) algorithm. This approach achieves more accurate estimates, closer to real observation data, by averaging the KL distribution. The algorithm is particularly well-suited for state estimation tasks in power systems that combine traditional and PMU measurements. Extensive simulations were conducted on the IEEE-14 and IEEE-30 test systems, and the results demonstrate that the fused estimator outperforms individual estimators in terms of estimation accuracy.
Full article
(This article belongs to the Special Issue Modeling of Quality, Reliability and Exploitation for Power Supply Systems - 2nd Edition)
Open AccessArticle
Performance Analysis and Optimization of Compressed Air Energy Storage Integrated with Latent Thermal Energy Storage
by
Xiaoli Yu, Wenbo Dou, Zhiping Zhang, Yan Hong, Gao Qian and Zhi Li
Energies 2024, 17(11), 2608; https://doi.org/10.3390/en17112608 - 28 May 2024
Abstract
Recovering compression waste heat using latent thermal energy storage (LTES) is a promising method to enhance the round-trip efficiency of compressed air energy storage (CAES) systems. In this study, a systematic thermodynamic model coupled with a concentric diffusion heat transfer model of the
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Recovering compression waste heat using latent thermal energy storage (LTES) is a promising method to enhance the round-trip efficiency of compressed air energy storage (CAES) systems. In this study, a systematic thermodynamic model coupled with a concentric diffusion heat transfer model of the cylindrical packed-bed LTES is established for a CAES system, and the numerical simulation model is validated by experimental data in the reference. Based on the numerical model, the charging–discharging performance of LTES and CAES systems is evaluated under different layouts of phase change materials (PCMs) in LTES, and the optimal layout of PCM is specified as a three-stage layout, since the exergy efficiency of LTES and round-trip efficiency are improved by 8.2% and 6.9% compared with a one-stage layout. Then, the proportion of three PCMs is optimized using response surface methods. The optimization results indicate that the exergy efficiency of LTES and round-trip efficiency of the CAES system are expected to be 80.9% and 73.3% under the PCM proportion of 0.48:0.3:0.22 for three stages, which are 7.0% and 13.1% higher than the original three-stage PCMs with equal proportions.
Full article
(This article belongs to the Special Issue Large-Scale Underground Energy Storage/Conversion Technologies Integrated with Renewable Energy Sources)
Open AccessArticle
Examination of Operational Methods for a Low-Temperature Aquifer Thermal Storage Air Conditioning System Based on Operational Performance and Considerations of Thermal Storage and Pumping Volume Balance
by
Linri Cui, Masatoshi Nishioka, Masaki Nakao and Kenji Ueda
Energies 2024, 17(11), 2607; https://doi.org/10.3390/en17112607 - 28 May 2024
Abstract
Aquifer Thermal Energy Storage (ATES) systems are garnering attention as high-efficiency air conditioning technologies that contribute to the realization of a carbon-neutral society. This study focuses on an ATES system constructed in Japan, characterized by its complex geological conditions and thin aquifer layers.
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Aquifer Thermal Energy Storage (ATES) systems are garnering attention as high-efficiency air conditioning technologies that contribute to the realization of a carbon-neutral society. This study focuses on an ATES system constructed in Japan, characterized by its complex geological conditions and thin aquifer layers. Detailed actual performance data measured over four years are presented, and performance analysis results show that a COP of 5 was achieved for the overall building cooling and heating system. In addition, the study provides a detailed analysis of the imbalance in heat quantity, remaining heat storage, and other factors based on actual data, identifying operational issues and summarizing specific improvement measures. Finally, as a proposal for a sustainable operational method to balance the cumulative heat storage and pumping volume of cold and hot water, specific operational procedures are summarized, including setting the return water temperature for the next season based on the dimensionless average pumping temperature of the previous season, and a flowchart is presented. There is no prior research that shows such specific operational procedures, and this can be considered an important achievement of this study.
Full article
(This article belongs to the Section H2: Geothermal)
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Open AccessArticle
Predictive Model for EV Charging Load Incorporating Multimodal Travel Behavior and Microscopic Traffic Simulation
by
Haihong Bian, Quance Ren, Zhengyang Guo, Chengang Zhou, Zhiyuan Zhang and Ximeng Wang
Energies 2024, 17(11), 2606; https://doi.org/10.3390/en17112606 - 28 May 2024
Abstract
A predictive model for the spatiotemporal distribution of electric vehicle (EV) charging load is proposed in this paper, considering multimodal travel behavior and microscopic traffic simulation. Firstly, the characteristic variables of travel time are fitted using advanced techniques such as Gaussian mixture distribution.
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A predictive model for the spatiotemporal distribution of electric vehicle (EV) charging load is proposed in this paper, considering multimodal travel behavior and microscopic traffic simulation. Firstly, the characteristic variables of travel time are fitted using advanced techniques such as Gaussian mixture distribution. Simultaneously, the user’s multimodal travel behavior is delineated by introducing travel purpose transfer probabilities, thus establishing a comprehensive travel spatiotemporal model. Secondly, the improved Floyd algorithm is employed to select the optimal path, taking into account various factors including signal light status, vehicle speed, and the position of starting and ending sections. Moreover, the approach of multi-lane lane change following and the utilization of cellular automata theory are introduced. To establish a microscopic traffic simulation model, a real-time energy consumption model is integrated with the aforementioned techniques. Thirdly, the minimum regret value is leveraged in conjunction with various other factors, including driving purpose, charging station electricity price, parking cost, and more, to simulate the decision-making process of users regarding charging stations. Subsequently, an EV charging load predictive framework is proposed based on the approach driven by electricity prices and real-time interaction of coupled network information. Finally, this paper conducts large-scale simulations to analyze the spatiotemporal distribution characteristics of EV charging load using a regional transportation network in East China and a typical power distribution network as case studies, thereby validating the feasibility of the proposed method.
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(This article belongs to the Section E: Electric Vehicles)
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Open AccessArticle
Novel Hierarchical Energy Management System for Enhanced Black Start Capabilities at Distribution and Transmission Networks
by
Ayse Colak, Mohamed Abouyehia and Khaled Ahmed
Energies 2024, 17(11), 2605; https://doi.org/10.3390/en17112605 - 28 May 2024
Abstract
A novel energy management system featuring a unique framework involving multiple hierarchical controllers at the distribution and transmission network levels is proposed. The unique objective function of this energy management system is designed to enhance system inertia during black start and optimise load
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A novel energy management system featuring a unique framework involving multiple hierarchical controllers at the distribution and transmission network levels is proposed. The unique objective function of this energy management system is designed to enhance system inertia during black start and optimise load shedding. The objective function further aims to increase reliance on renewable energy sources, prioritising solar power along with battery and fuel cell technologies. This work delves deeply into the dynamics of multi-area power networks, where some areas possess black start capabilities (BSAs) while others do not (NBSAs). The proposed energy management system specifically explores the complex interplay between these black start capabilities and the hierarchical load restoration order. During grid blackouts, the systems located in BSA areas are tasked with first restoring essential loads in their own regions before extending aid to the adjacent NBSA areas, taking into account factors such as their available reserved power and geographical proximity. This work is extended to analyse complex multi-area power network architectures. This extended analysis provides invaluable insights for enhancing power restoration processes and facilitating the large-scale integration of sustainable energy solutions in complex systems. The proposed energy management system is validated using the IEEE 39-Bus network, which consists of ten distinct areas, each differing in their black start capabilities. The results demonstrate the superiority of the proposed system.
Full article
(This article belongs to the Special Issue Energy, Electrical and Power Engineering 2024)
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Open AccessArticle
Comparisons of Different Representative Species Selection Schemes for Reduced-Order Modeling and Chemistry Acceleration of Complex Hydrocarbon Fuels
by
Kevin M. Gitushi and Tarek Echekki
Energies 2024, 17(11), 2604; https://doi.org/10.3390/en17112604 - 28 May 2024
Abstract
The simulation of engine combustion processes, such as autoignition, an important process in the co-optimization of fuel-engine design, can be computationally expensive due to the large number of thermo-chemical scalars needed to describe the full chemical system. Yet, the inherent correlations between the
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The simulation of engine combustion processes, such as autoignition, an important process in the co-optimization of fuel-engine design, can be computationally expensive due to the large number of thermo-chemical scalars needed to describe the full chemical system. Yet, the inherent correlations between the different chemical species during oxidation can significantly reduce the complexity of representing this system. One strategy is to select a subset of representative species that accurately captures the combustion process at a fraction of the computational cost of the full system. In this study, we compare the performance of four different techniques to select these species. They include the two-step principal component analysis (PCA) approach, directed relation graphs (DRGs), the global pathway selection (GPS) approach, and the manifold-informed species selection method. A parametric study of the representative species selection is carried out on data from the simulation of homogeneous and perfectly stirred reactors by investigating seven cumulative variances and 47 different cut-off percentages for the two-step PCA, and 65 and 51 thresholds for the DRGs and GPS, respectively. Results show that these selection methods capture key important species that can accurately describe the chemical system and track each stage of oxidation. The two-step PCA is sensitive to the cumulative variance, and DRGs and GPS are sensitive to the choice of target variables. By selecting key representative species and reducing the number of thermo-chemical scalars, these three methods can be used to develop computationally efficient hybrid chemistry schemes.
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(This article belongs to the Topic Theoretical, Numerical and Experimental Studies on Clean Energy and Combustion)
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Open AccessArticle
Numerical and Thermodynamic Analysis of the Effect of Operating Temperature in Methane-Fueled SOFC
by
Berre Kumuk, Nisa Nur Atak, Battal Dogan, Salih Ozer, Pinar Demircioglu and Ismail Bogrekci
Energies 2024, 17(11), 2603; https://doi.org/10.3390/en17112603 - 28 May 2024
Abstract
This study examines the thermodynamic and numerical analyses of a methane-fed solid oxide fuel cell (SOFC) over a temperature range varying between 873 K and 1273 K. These analyses were conducted to investigate and compare the performance of the SOFC under various operating
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This study examines the thermodynamic and numerical analyses of a methane-fed solid oxide fuel cell (SOFC) over a temperature range varying between 873 K and 1273 K. These analyses were conducted to investigate and compare the performance of the SOFC under various operating conditions in detail. As part of the thermodynamic analysis, important parameters such as cell voltage, power density, exergy destruction, entropy generation, thermal efficiency, and exergy efficiency were calculated. These calculations were used to conduct energy and exergy analyses of the cell. According to the findings, an increase in operating temperature led to a significant improvement in performance. At the initial conditions where the SOFC operated at a temperature of 1073 K and a current density of 9000 A/m2, it was observed that when the temperature increased by 200 K while keeping the current density constant, the power density increased by a factor of 1.90 compared to the initial state, and the thermal efficiency increased by a factor of 1.45. Under a constant current density, the voltage and power density values were 1.0081 V, 1.0543 V, 2337.13 W/m2, and 2554.72 W/m2 at operating temperatures of 1073 K and 1273 K, respectively. Under a current density of 4500 A/m2, the entropy generation in the cell was determined to be 29.48 kW/K at 973 K and 23.68 kW/K at 1173 K operating temperatures. The maximum exergy efficiency of the SOFC was calculated to be 41.67% at a working temperature of 1273 K and a current density of 1500 A/m2. This study is anticipated to be highly significant, as it examines the impact of temperature variation on exergy analysis in SOFC, validating both numerical and theoretical results, thus providing a crucial roadmap for determining optimized operating conditions.
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(This article belongs to the Section I: Energy Fundamentals and Conversion)
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Open AccessArticle
Assessing the Potential for Electrification of the Food Industry and Its Implications for Environmental Sustainability
by
Yoann Jovet, Alexis Laurent, Frédéric Lefevre and Marc Clausse
Energies 2024, 17(11), 2602; https://doi.org/10.3390/en17112602 - 28 May 2024
Abstract
Most studies on industrial heat decarbonization by electrification focus on energy and greenhouse gas emissions. However, there are additional potential environmental impacts to be considered to make a fair comparison. The aim of the proposed work is therefore to highlight the benefits and
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Most studies on industrial heat decarbonization by electrification focus on energy and greenhouse gas emissions. However, there are additional potential environmental impacts to be considered to make a fair comparison. The aim of the proposed work is therefore to highlight the benefits and drawbacks of switching to electricity, using life cycle assessment (LCA) methodology to explore more environmental issues. In addition, in order to evaluate the environmental sustainability of this transformation, the LCA results are compared with sustainability thresholds defined with two different methods, on a global scale using the “sustainable levels” concept. The first method is based on the current environmental impacts of industrial processes, while the second considers the economic added value. Industrial heat production levels for the Danish and French food industries are used as case studies. The results show a large number of environmental trade-offs associated with electrification, some of which are leading to unsustainable levels. Sustainability thresholds based on economic added value ensure a fairer distribution between sectors, in particular by preventing the most virtuous sectors and processes from being penalized.
Full article
(This article belongs to the Topic Sustainable Energy: Efficient Technological Solutions Combining Environmental, Economic, Political and Social Aspects)
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Open AccessArticle
Analysis of the Hybrid Power-Heating System in a Single-Family Building, along with Ecological Aspects of the Operation
by
Grzegorz Woroniak, Joanna Piotrowska-Woroniak, Anna Woroniak, Edyta Owczarek and Krystyna Giza
Energies 2024, 17(11), 2601; https://doi.org/10.3390/en17112601 - 28 May 2024
Abstract
This study evaluates a hybrid heating system in a single-family building in northeastern Poland, which has a temperate continental climate. The analysis covers two heating seasons in 2021/2022 and 2022/2023. The hybrid heating system includes an air heat pump HPA–08 CS Plus with
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This study evaluates a hybrid heating system in a single-family building in northeastern Poland, which has a temperate continental climate. The analysis covers two heating seasons in 2021/2022 and 2022/2023. The hybrid heating system includes an air heat pump HPA–08 CS Plus with a heating power of 8.2 kW (AHP), a condensing gas boiler VC146/5–5 with a power of 14 kW (GB–Condens.), and a solid fuel boiler with a power of 11 kW for central heating. Additionally, hot water is heated by a Basic 270 (DHW’s AHP) air–water heat pump with a power of 2 kW, utilizing a tank with a capacity of 270 dm3 equipped with two heating coils. The building’s average electricity consumption is around 5400 kWh/year. A 4.96 kWp photovoltaic installation is installed on the building’s roof at a 40° angle towards the south to supplement the hybrid system. The study aims to assess whether the PV installation can adequately cover the energy needs of the hybrid heat source for heating and hot water. Furthermore, the study calculates the emission of pollutants (CO2, SOx, NOx, CO, and PM10) into the atmosphere. The total annual electricity production from PV installations was 5444.9 kWh in 2021/2022 and 5684.8 kWh in 2022/2023. The excess electricity was stored in the PGE power grid as per the Prosumer settlement rules. The installed PV installation is sufficient to power the following devices annually: AHP, DHW’s AHP, and GB–Condens. However, the daily electricity production from the PV installation is not enough to cover the energy needs of the heat pump for heating during the cold months in Poland (I–III, XI–XII). It can meet the power needs of a PC all year round and can also be stored during the summer months, for example, in energy warehouses or by directly storing it in the PGE power grid. The use of the PV installation resulted in an average reduction in pollutant emissions into the atmosphere: CO2—94.1%, SOx—91.8%, NOx—95.6%, CO—9.7%, and PM10—32.1%.
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(This article belongs to the Special Issue Optimization and Innovation of Energy Efficient Buildings and Smart Cities)
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Open AccessArticle
Experimental Investigation of the Impact of CO2 Injection Strategies on Rock Wettability Alteration for CCS Applications
by
Stella I. Eyitayo, Gamadi Talal, Oladoyin Kolawole, Chinedu J. Okere, Ion Ispas, Nachiket Arbad, Hossein Emadibaladehi and Marshall C. Watson
Energies 2024, 17(11), 2600; https://doi.org/10.3390/en17112600 - 28 May 2024
Abstract
Carbon capture and storage (CCS) has been recognized as a pivotal technology for mitigating climate change by reducing CO2 emissions. Storing CO2 in deep saline aquifers requires preserving the water-wet nature of the formation throughout the storage period, which is crucial
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Carbon capture and storage (CCS) has been recognized as a pivotal technology for mitigating climate change by reducing CO2 emissions. Storing CO2 in deep saline aquifers requires preserving the water-wet nature of the formation throughout the storage period, which is crucial for maintaining rock integrity and storage efficiency. However, the wettability of formations can change upon exposure to supercritical CO2 (scCO2), potentially compromising storage efficiency. Despite extensive studies on various factors influencing wettability alteration, a significant research gap remains in understanding the effects of different CO2 injection strategies on wettability in deep saline formations (DSFs). This study addresses this gap by investigating how three distinct CO2 injection strategies—continuous scCO2 injection (CCI), water alternating with scCO2 injection (WAG), and simultaneous water and scCO2 injection (SAI)—affect the wettability of gray Berea sandstone and Indiana limestone, both selected for their homogeneous properties relevant to CCS. Using a standardized sessile drop contact angle method before and after CO2 injection, along with core flooding to model the injection process at an injection pressure of 1500 psi and temperature of 100 °F with a confining pressure of 2500 psi, the results indicate a shift in wettability towards more CO2-wet conditions for both rock types under all strategies with changes in CA of 61.6–83.4° and 77.6–87.9° and 81.5–124.2° and 94.6–128.0° for sandstone and limestone, respectively. However, the degree of change varies depending on the injection strategy: sandstone exhibits a pronounced response to the CCI strategy, with up to a 77% increase in contact angle (CA), particularly after extended exposure. At the same time, WAG shows the least change, suggesting that water introduction slows surface modification. For limestone, the changes in CA ranged from 9% to 49% across strategies, with WAG and SAI being more effective in altering its wettability. This study underscores the importance of selecting suitable CO2 injection strategies based on rock type and wettability characteristics to maximize carbon storage efficiency. The findings offer valuable insights into the complex interactions of fluid–rock systems and a guide for enhancing the design and implementation of CCS technologies in various geological settings.
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(This article belongs to the Special Issue Subsurface Energy and Environmental Protection)
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Open AccessArticle
Life Cycle Assessment of a Wood Biomass Gasification Plant and Implications for Syngas and Biochar Utilization
by
Francesco Arfelli, Cristian Tosi, Luca Ciacci and Fabrizio Passarini
Energies 2024, 17(11), 2599; https://doi.org/10.3390/en17112599 - 28 May 2024
Abstract
The growing attention regarding the environmental challenges in the energy sectors pushes the industrial system toward the investigation of more sustainable and renewable energy sources to replace fossil ones. Among the promising alternatives, biomass is considered a valid source to convert the system
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The growing attention regarding the environmental challenges in the energy sectors pushes the industrial system toward the investigation of more sustainable and renewable energy sources to replace fossil ones. Among the promising alternatives, biomass is considered a valid source to convert the system and to reduce the fossil fraction of the national energy mixes, but its multiple potential uses need an environmental evaluation to understand the actual benefit when it is used as an energy resource. For this purpose, life cycle assessment (LCA) is applied to a wood biomass gasification system aimed to produce electricity and heat generated after the combustion of the produced syngas and the management of the biochar. The aim is to provide a quantitative comparison of (i) a baseline scenario where wood biomass is sourced from waste and (ii) a second scenario where wood biomass is drawn from dedicated cultivation. A further evaluation was finally applied to investigate the environmental implications associated with the biochar composition, assuming it was used on land. The proposed strategies resulted in an environmental credit for both the examined scenarios, but the outcomes showed a net preference for the baseline scenario, resulting in better environmental performances for all the examined categories with respect to the second one. It underlines the potentialities of using waste-sourced biomass. However, according to the Climate Change category, if on-site dedicated biomass cultivation is assumed for the second scenario, the baseline is considered preferable only if the biomass transportation distance is <600 km, which is estimated as a theoretical distance for scenarios to break even. Finally, biochar composition proved a particular concern for toxicity-related categories. This study highlights the importance of applying objective and standardized methodologies such as LCA to evaluate energy production systems based on alternative sources and to support decision-making toward achieving sustainability goals.
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(This article belongs to the Section B: Energy and Environment)
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Open AccessArticle
Detection of Cavitation in a Centrifugal Pump-as-Turbine Using Time-Domain-Based Analysis of Vibration Signals
by
Calvin Stephen, Biswajit Basu and Aonghus McNabola
Energies 2024, 17(11), 2598; https://doi.org/10.3390/en17112598 - 28 May 2024
Abstract
Pumps-as-Turbines (PATs) are increasingly used in micro-hydropower applications due to their cost competitiveness that is brought about by lower acquisition, design, operation, and maintenance costs. Despite these, limited research exists that investigates PAT failures. Notably, there is a literature gap concerning cavitation in
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Pumps-as-Turbines (PATs) are increasingly used in micro-hydropower applications due to their cost competitiveness that is brought about by lower acquisition, design, operation, and maintenance costs. Despite these, limited research exists that investigates PAT failures. Notably, there is a literature gap concerning cavitation in PATs. As such, this study proposes an improvement to the deviation from the normal distribution (DND) technique to facilitate application in PAT cavitation detection. Probability density functions of vibration signals collected during operation at design speed and various cavitation states are developed and the DND computed using two approaches, i.e., the use of baseline data and the original method, for comparison purposes. Normal probability plots are presented to depict suitability of the two approaches in quantifying the DND. Results show higher deviation when using baseline data, hence, improved detection capabilities with amplification of the slope of the trend line under cavitating conditions when using the proposed DND approach. The proposed method also allows for establishing clear alarm limits for the condition monitoring of PATs in practice. Moreover, the proposed method is validated by application at various PAT operating speeds and cavitation states. The proposed method is found to be responsive, reliable, and independent from operating speed.
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(This article belongs to the Section A3: Wind, Wave and Tidal Energy)
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Open AccessEditorial
Porous Flow of Energy and CO2 Transformation and Storage in Deep Formations: An Overview
by
Rui Song and Jianjun Liu
Energies 2024, 17(11), 2597; https://doi.org/10.3390/en17112597 - 28 May 2024
Abstract
The transformation and storage of energy and carbon dioxide in deep reservoirs include underground coal gasification, the underground storage of oil and gas, the underground storage of hydrogen, underground compressed air energy storage, the geological utilization and storage of carbon dioxide, etc [...]
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The transformation and storage of energy and carbon dioxide in deep reservoirs include underground coal gasification, the underground storage of oil and gas, the underground storage of hydrogen, underground compressed air energy storage, the geological utilization and storage of carbon dioxide, etc [...]
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(This article belongs to the Topic Porous Flow of Energy & CO2 Transformation and Storage in Deep Formations)
Open AccessArticle
Carbon Pricing Impacts on Four Pollutants: A Cross-Country Analysis
by
Rohan Best, Fatemeh Nazifi and Han Cheng
Energies 2024, 17(11), 2596; https://doi.org/10.3390/en17112596 - 28 May 2024
Abstract
Research on climate change mitigation has increasingly considered carbon pricing, with these efforts concentrating on reductions in carbon dioxide (CO2) emissions. Our comprehensive cross-country analysis extends this focus by quantitatively evaluating the effects of carbon pricing on four major pollutants: CO
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Research on climate change mitigation has increasingly considered carbon pricing, with these efforts concentrating on reductions in carbon dioxide (CO2) emissions. Our comprehensive cross-country analysis extends this focus by quantitatively evaluating the effects of carbon pricing on four major pollutants: CO2, nitrous oxide (N2O), methane (CH4), and particulate matter (PM). We use regressions and introduce entropy balancing to this research area. Analyzing data from 132 countries from 1992 to 2019, we find that carbon pricing is associated with an average annual reduction in CO2 emissions by 3 percentage points. A one-unit increase in a coverage-weighted carbon price is associated with reductions in N2O emissions by approximately 0.1 percentage points. A shorter panel for 2010–2017 shows a larger impact of 0.3 percentage points for PM. These findings underline the efficacy of carbon pricing not just in curtailing CO2 but in significantly mitigating other harmful pollutants on a global scale. Reductions in pollutants beyond CO2 provide further motivation for policymakers to pursue carbon pricing.
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(This article belongs to the Section C: Energy Economics and Policy)
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Open AccessReview
Analysis of Model Predictive Control-Based Energy Management System Performance to Enhance Energy Transmission
by
Israth Jahan Chowdhury, Siti Hajar Yusoff, Teddy Surya Gunawan, Suriza Ahmad Zabidi, Mohd Shahrin Bin Abu Hanifah, Siti Nadiah Mohd Sapihie and Bernardi Pranggono
Energies 2024, 17(11), 2595; https://doi.org/10.3390/en17112595 - 28 May 2024
Abstract
A supervisory control system using Model Predictive Control (MPC) has been designed to evaluate the efficiency of wind and solar power and is consistent with the cost function in the supervisory MPC optimization problem. A two-layer Economic Model Predictive Control (EMPC) framework has
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A supervisory control system using Model Predictive Control (MPC) has been designed to evaluate the efficiency of wind and solar power and is consistent with the cost function in the supervisory MPC optimization problem. A two-layer Economic Model Predictive Control (EMPC) framework has been developed and has improved results such as cost reductions compared to recent advanced methods. A speed Generalized Predictive Control (GPC) scheme intended for wind energy conversion systems was developed last year, with simulation results indicating superior performance over previous models. A Hierarchical Distributed Model Predictive Control (HDMPC) can work under different weather conditions with improved economic performance and keep a good balance between power delivery and load demand. An energy management system (EMS), built on the basis of MPC, can be quite lucrative for the sphere in the present climate scenario, with the selection and testing of suitable algorithms, controlled processes, cost functions, and a set of constraints as well as with proper optimizations carried out. Previous research indicates that an MPC-based EMS has the potential to be a good solution to manage energy well and also introduced it to the world experimentally. The key intention of this research study is to explore the existing advances that have been introduced and to analyze their performance in terms of cost function, different sets of constraints, variant conversion processes, and scalability to achieve more optimized operation of MPC-based EMS.
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(This article belongs to the Special Issue Internet of Things, Edge Computing, and Artificial Intelligence for Smart Grid—2nd Edition)
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Open AccessArticle
Simulation and Characterization of Micro-Discharge Phenomena Induced by Glitch Micro-Defects on an Insulated Pull Rod Surface
by
Shu Niu, Shuai Li, Jizhong Liang, Guodong Li, Fan Hu, Hai Zhang, Yujie Zhu, Xianhao Fan and Chuanyang Li
Energies 2024, 17(11), 2594; https://doi.org/10.3390/en17112594 - 28 May 2024
Abstract
The reliability of GIS (gas-insulated switchgear) circuit breakers significantly depends on the condition of the insulated pull rods, with micro-defects on their surface posing a potential risk for micro-discharges and breakdown incidents. Experimentally investigating these micro-discharges is challenging due to their minute nature.
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The reliability of GIS (gas-insulated switchgear) circuit breakers significantly depends on the condition of the insulated pull rods, with micro-defects on their surface posing a potential risk for micro-discharges and breakdown incidents. Experimentally investigating these micro-discharges is challenging due to their minute nature. This study introduces a framework to examine the linkage between micro-defects and micro-discharges, coupled with numerical simulations of the micro-discharge process in insulated pull rods afflicted by surface infiltration flaws under operational conditions. Initially, samples containing micro-defects were sectioned via water jet cutting for microstructural analysis through white light interferometry. Subsequently, a two-dimensional axisymmetric model simulating positive corona discharge from a needle to a plate electrode was employed to derive the relationship between charged particle density and the electric field in SF6 and air. Building on these observations, a micro-discharge model specific to micro-defects was developed. Comparative analysis of micro-discharge behaviors in SF6 and air for identical defect types was conducted. This research framework elucidates the discharge dynamics of charged particles in SF6 and air during micro-discharge events, shedding light on the mechanisms underpinning micro-discharges triggered by insulation rod defects.
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(This article belongs to the Special Issue Advanced Power Electronics Technology)
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Open AccessArticle
Studying the Optimal Frequency Control Condition for Electric Vehicle Fast Charging Stations as a Dynamic Load Using Reinforcement Learning Algorithms in Different Photovoltaic Penetration Levels
by
Ibrahim Altarjami and Yassir Alhazmi
Energies 2024, 17(11), 2593; https://doi.org/10.3390/en17112593 - 28 May 2024
Abstract
This study investigates the impact of renewable energy penetration on system stability and validates the performance of the (Proportional-Integral-Derivative) PID-(reinforcement learning) RL control technique. Three scenarios were examined: no photovoltaic (PV), 25% PV, and 50% PV, to evaluate the impact of PV penetration
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This study investigates the impact of renewable energy penetration on system stability and validates the performance of the (Proportional-Integral-Derivative) PID-(reinforcement learning) RL control technique. Three scenarios were examined: no photovoltaic (PV), 25% PV, and 50% PV, to evaluate the impact of PV penetration on system stability. The results demonstrate that while the absence of renewable energy yields a more stable frequency response, a higher PV penetration (50%) enhances stability in tie-line active power flow between interconnected systems. This shows that an increased PV penetration improves frequency balance and active power flow stability. Additionally, the study evaluates three control scenarios: no control input, PID-(Particle Swarm Optimization) PSO, and PID-RL, to validate the performance of the PID-RL control technique. The findings show that the EV system with PID-RL outperforms the other scenarios in terms of frequency response, tie-line active power response, and frequency difference response. The PID-RL controller significantly enhances the damping of the dominant oscillation mode and restores the stability within the first 4 s—after the disturbance in first second. This leads to an improved stability compared to the EV system with PID-PSO (within 21 s) and without any control input (oscillating more than 30 s). Overall, this research provides the improvement in terms of frequency response, tie-line active power response, and frequency difference response with high renewable energy penetration levels and the research validates the effectiveness of the PID-RL control technique in stabilizing the EV system. These findings can contribute to the development of strategies for integrating renewable energy sources and optimizing control systems, ensuring a more stable and sustainable power grid.
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(This article belongs to the Special Issue Application of Intelligent Techniques in Power System Stability, Control and Protection)
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