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
Laboratory Tests of Electrical Parameters of the Start-Up Process of Single-Cylinder Diesel Engines
Energies 2024, 17(9), 2155; https://doi.org/10.3390/en17092155 (registering DOI) - 30 Apr 2024
Abstract
Despite continuous work on new power systems for vehicles, machines, and devices, the combustion engine is still the dominant system. The operation of the combustion engine is initiated during the starting process using starting devices. The most common starting system used is the
[...] Read more.
Despite continuous work on new power systems for vehicles, machines, and devices, the combustion engine is still the dominant system. The operation of the combustion engine is initiated during the starting process using starting devices. The most common starting system used is the electric starter. The starting process of an internal combustion engine depends on the following factors: the technical condition of the starting system, technical condition of the engine, battery charge level, lubricating properties, engine standstill time, engine and ambient temperature, type of fuel, etc. This article presents the results of laboratory tests of the electrical parameters of the starting process of a single-cylinder compression–ignition engine with variable fuel injection parameters and ambient temperature conditions. It was confirmed that for the increased fuel dose FD2, higher values of the measured electrical parameters (Imax, Pmax, and Pmed) were obtained compared to the series of tests with the nominal fuel dose. Knowledge of the values of the electrical parameters of the starting process is important not only for the user (vehicle driver, agricultural machinery operator, etc.), but above all for designers of modern starting systems for combustion engines and service personnel. The obtained results of testing the electrical parameters of the combustion engine during start-up may be helpful in designing new drive systems supported by a compression–ignition combustion engine.
Full article
(This article belongs to the Special Issue Internal Combustion Engine: Research and Application—2nd Edition)
Open AccessArticle
Health State Assessment of Lithium-Ion Batteries Based on Multi-Health Feature Fusion and Improved Informer Modeling
by
Jun He, Xinyu Liu, Wentao Huang, Bohan Zhang, Zuoming Zhang, Zirui Shao and Zimu Mao
Energies 2024, 17(9), 2154; https://doi.org/10.3390/en17092154 (registering DOI) - 30 Apr 2024
Abstract
Accurately assessing the state of health (SOH) of lithium batteries is of great significance for improving battery safety performance. However, the current assessment for SOH suffers from the difficulty of selecting health features and the lack of uncertainty using data-driven methods. To this
[...] Read more.
Accurately assessing the state of health (SOH) of lithium batteries is of great significance for improving battery safety performance. However, the current assessment for SOH suffers from the difficulty of selecting health features and the lack of uncertainty using data-driven methods. To this end, this paper proposes a health state assessment method for lithium-ion batteries based on health feature extraction and an improved Informer model. First, multiple features that can reflect the SOH of lithium-ion batteries were extracted from the charging and discharging time, the peak value of incremental capacity curve (ICC), and the inflection point value of differential voltage curve, etc., and the correlation between multiple health features and the health state was evaluated by gray correlation analysis. Then, an improved Informer model is proposed to establish a health state estimation method for lithium-ion batteries. Finally, the proposed algorithm is tested and validated using publicly available battery charge/discharge datasets and compared with other algorithms. The results show that the method in this paper can realize high-precision SOH prediction with a root-mean-square error (RMSE) of 0.011, and the model fit reaches more than 98%.
Full article
(This article belongs to the Section D: Energy Storage and Application)
Open AccessArticle
Investigation of the Combustion Properties of Ethylene in Porous Materials Using Numerical Simulations
by
Linyu Tu, Siyu Ding, Shefeng Li, Haitao Zhang and Wei Feng
Energies 2024, 17(9), 2153; https://doi.org/10.3390/en17092153 (registering DOI) - 30 Apr 2024
Abstract
As industrial modernization advances rapidly, the need for energy becomes increasingly urgent. This paper aims to enhance the current burner design by optimizing the combustion calorific value, minimizing pollutant emissions, and validating the accuracy of the burner model using experimental data from previous
[...] Read more.
As industrial modernization advances rapidly, the need for energy becomes increasingly urgent. This paper aims to enhance the current burner design by optimizing the combustion calorific value, minimizing pollutant emissions, and validating the accuracy of the burner model using experimental data from previous studies. The enhanced porous medium burner model is used to investigate the burner’s combustion and pollutant emission characteristics at various flow rates, equivalence ratios, combustion orifice sizes, and porosity of porous media. In comparison with the previous model, the combustion traits during ethylene combustion and the emission properties of pollutants under various operational circumstances have been enhanced with the enhanced porous medium burner model. The maximum temperature of ethylene combustion in the enhanced model is 174 k higher than that before the improvement, and the CO emissions are reduced by 31.9%. It is believed that the findings will serve as a guide for the practical implementation of porous media combustion devices.
Full article
(This article belongs to the Section I2: Energy and Combustion Science)
►▼
Show Figures
Figure 1
Open AccessArticle
Design and Experimental Tests of a Four-Way Valve with the Determination of Flow Characteristics for Building Central Heating Installations Using Solid Modeling
by
Mariusz Niekurzak and Jerzy Mikulik
Energies 2024, 17(9), 2152; https://doi.org/10.3390/en17092152 (registering DOI) - 30 Apr 2024
Abstract
The article presents the design of a four-way valve, implemented in SolidWorks software (SOLIDWORKS® i 3DEXPERIENCE® Works Simulation) and used for central heating installations in buildings. The project was carried out in order to examine the innovative design of the medium
[...] Read more.
The article presents the design of a four-way valve, implemented in SolidWorks software (SOLIDWORKS® i 3DEXPERIENCE® Works Simulation) and used for central heating installations in buildings. The project was carried out in order to examine the innovative design of the medium mixing mechanism and to conduct strength and FMEA analysis. The innovative solutions proposed by the authors in this work will allow valves of this type to meet stringent environmental standards. These standards are currently being introduced for this type of structural element of machine parts as part of the energy transformation of buildings. Potential failures occurring in individual elements of the four-way valve were also tested using Failure mode and effects analysis. In addition, strength tests were performed in SolidWorks software using static analysis, and optimization tests were performed on the refrigerant in terms of its impact on the environment. The characteristics of the tested materials in the valve design show that the best materials are brass and stainless steel. Brass has a Poisson’s ratio of 0.33, a tensile strength of 478.4 MPa and a yield strength of 239.7 MPa. In turn, stainless steel is characterized by the following parameters: Poisson’s ratio of 0.27, tensile strength of 685 MPa and yield strength of 292 MPa. The designed valve reduces energy consumption by 30% through a properly designed medium flow with the appropriate selection of materials. Moreover, the design reduces the thickness of the contaminant layer by 0.17 mm, with a capacity factor of −2.50% and an evaporator Δp of 3.10% (53 kPa). The performed research provides knowledge on the subject selection of appropriate material, a description of the potential failures of the structural elements of the designed four-way valve and methods of counteracting these failures. The article presents the optimization role of the tested component in the context of sustainable development.
Full article
(This article belongs to the Special Issue Latest Research on Heat and Mass Transfer in Buildings)
Open AccessArticle
Global Genetic Algorithm for Automating and Optimizing Petroleum Well Deployment in Complex Reservoirs
by
Sonny Irawan, Dennis Delali Kwesi Wayo, Alfrendo Satyanaga and Jong Kim
Energies 2024, 17(9), 2151; https://doi.org/10.3390/en17092151 (registering DOI) - 30 Apr 2024
Abstract
Locating petroleum-productive wells using informed geological data, a conventional means, has proven to be tedious and undesirable by reservoir engineers. The former numerical simulator required a lengthy trial-and-error process to manipulate the variables and uncertainties that lie on the reservoir to determine the
[...] Read more.
Locating petroleum-productive wells using informed geological data, a conventional means, has proven to be tedious and undesirable by reservoir engineers. The former numerical simulator required a lengthy trial-and-error process to manipulate the variables and uncertainties that lie on the reservoir to determine the best placement of the well. Hence, this paper examines the use of a global genetic algorithm (GA) to optimize the placement of wells in complex reservoirs, rather than relying on gradient-based (GB) methods. This is because GB approaches are influenced by the solution’s surface gradient and may only reach local optima, as opposed to global optima. Complex reservoirs have rough surfaces with high uncertainties, which hinders the traditional gradient-based method from converging to global optima. The explicit focus of this study was to examine the impact of various initial well placement distributions, the number of random solution sizes and the crossover rate on cumulative oil production, the optimization of the synthetic reservoir model created by CMG Builder, CMOST, and IMEX indicated that using a greater number of random solutions led to an increase in cumulative oil production. Despite the successful optimization, more generations are required to reach the optimal solution, while the application of GA on our synthetic model has proven efficient for well placement; however, different optimization algorithms such as the improved particle swarm (PSO) and grey wolf optimization (GWO) algorithms could be used to redefine well-placement optimization in CMG.
Full article
(This article belongs to the Special Issue New Insights into Reservoir 3D Modeling and Simulation)
Open AccessArticle
Novel Advanced Artificial Neural Network-Based Online Stator and Rotor Resistance Estimator for Vector-Controlled Speed Sensorless Induction Motor Drives
by
Ajithanjaya Kumar Mijar Kanakabettu, Rajkiran Ballal Irvathoor, Sanath Saralaya, Sathyendra Bhat Jodumutt and Athokpam Bikramjit Singh
Energies 2024, 17(9), 2150; https://doi.org/10.3390/en17092150 (registering DOI) - 30 Apr 2024
Abstract
This paper presents a new approach for the online estimation of stator and rotor resistance of induction motors for speed sensorless vector-controlled drives, using feed-forward artificial neural networks with advanced adaptive learning rates. For the rotor resistance estimation, a neural network model based
[...] Read more.
This paper presents a new approach for the online estimation of stator and rotor resistance of induction motors for speed sensorless vector-controlled drives, using feed-forward artificial neural networks with advanced adaptive learning rates. For the rotor resistance estimation, a neural network model based on rotor speed and stator currents is developed. The rotor flux linkages acquired from the voltage model are compared with the neural network model. The feed-forward neural network employs an adaptive learning rate as the function of the obtained error during training for quick convergence with minimal estimation error. A two-layered neural network model based on the stator voltage and current equations is developed for the stator resistance estimation. The d-q axes stator currents obtained from the developed model are compared with the acquired d-q axes stator currents. For the fast convergence with minimal estimation error, an adaptive learning rate as the function of error is adopted during training. Furthermore, the neural network estimates the induction motor’s speed. The simulation and experimental results justify that the developed algorithms track variation in the resistances quickly and precisely along with the speed as compared with the conventional constant learning rate algorithm, leading to reliable operation of the drive.
Full article
(This article belongs to the Section F: Electrical Engineering)
Open AccessArticle
Low-Salinity Waterflooding for EOR in Field A of Western Offshore Basin: A Pilot Study Analysis with Laboratory and Simulation Studies—Early Observations
by
Vivek Raj Srivastava, Hemanta K. Sarma and Sharad Kumar Gupta
Energies 2024, 17(9), 2149; https://doi.org/10.3390/en17092149 (registering DOI) - 30 Apr 2024
Abstract
Carbonate reservoirs hold vast oil reserves, but their complex properties make traditional enhanced oil recovery (EOR) methods challenging. This study explores the application of low-salinity water flooding (LSWF) as a novel EOR method for India’s largest offshore carbonate oil field. Conventional EOR techniques
[...] Read more.
Carbonate reservoirs hold vast oil reserves, but their complex properties make traditional enhanced oil recovery (EOR) methods challenging. This study explores the application of low-salinity water flooding (LSWF) as a novel EOR method for India’s largest offshore carbonate oil field. Conventional EOR techniques were deemed unsuitable due to reservoir heterogeneity, pressure decline, high temperature, and the offshore location. Favorable factors for LSWF included successful seawater flooding history, medium-weight crude oil, and existing infrastructure. Following core flooding experiments demonstrating a 6–16% increase in oil recovery, a multi-pronged evaluation process was implemented. Single-well chemical tracer tests (SWCTT) and reservoir simulations confirmed the potential of LSWF. A specific target area was chosen based on reservoir characteristics, production data, and available facilities. Simulations predicted a 1.5% incremental oil recovery using diluted seawater (25% salinity) at 30% pore volume injection. After a positive techno-economic analysis, the first offshore LSWF project in India was completed within 3 years. Initial monitoring results are encouraging. This study highlights the successful journey of LSWF from concept to field deployment in a challenging carbonate reservoir, showcasing its potential for revitalizing such fields. Furthermore, this work provides valuable data relevant to Indian offshore environments, where factors like salinity, mineralogy, and crude oil composition pose unique challenges compared to other LSWF applications. These detailed data fill a critical gap in the existing literature.
Full article
(This article belongs to the Section I1: Fuel)
Open AccessArticle
Classification of Smart and Sustainable Urban Mobility
by
Aleksandra Gulc and Klaudia Budna
Energies 2024, 17(9), 2148; https://doi.org/10.3390/en17092148 (registering DOI) - 30 Apr 2024
Abstract
The main purpose of this article is to identify and classify smart and sustainable urban mobility solutions in the context of three narratives for sustainable mobility: electromobility, collective transport 2.0 and low-mobility societies. The research process of this study included the following methods:
[...] Read more.
The main purpose of this article is to identify and classify smart and sustainable urban mobility solutions in the context of three narratives for sustainable mobility: electromobility, collective transport 2.0 and low-mobility societies. The research process of this study included the following methods: review of the literature, namely, strategic European documents, sustainable urban mobility plans in chosen cities and scientific publications addressing smart and sustainable mobility, case studies of selected cities in Europe and technology mapping to visualize the study results. The main result of this study is the review of various smart and sustainable urban solutions (SSUM) and their classification within the three narratives of electromobility, collective transport 2.0 and low-mobility societies. This article expands the concept of the three narratives for sustainable mobility with the aspect of smart mobility enriched with the variety of example solutions, case studies and good practices within mobility strategies in European cities. The study results can be useful for different stakeholders engaged in developing and introducing the sustainable mobility strategies in cities. Based on the catalogue of SSUM solutions, presented case studies and good practices, they may gain the necessary knowledge, consider the possible initiatives towards green transformation in cities and finally adjust them to the citizens’ need.
Full article
(This article belongs to the Special Issue Advances in Energy Transition in Transport and Logistics in Modern, Low-Emission, Smart and Sustainable Cities)
Open AccessArticle
Definition of Regulatory Targets for Electricity Default Rate in Brazil: Proposition of a Fuzzy Inference-Based Model
by
Nivia Maria Celestino, Rodrigo Calili, Daniel Louzada and Maria Fatima Almeida
Energies 2024, 17(9), 2147; https://doi.org/10.3390/en17092147 (registering DOI) - 30 Apr 2024
Abstract
The current electricity default rates in continental countries, such as Brazil, pose risks to the economic stability and investment capabilities of distribution utilities. This situation results in higher electricity tariffs for regular customers. From a regulatory perspective, the key issue regarding this challenge
[...] Read more.
The current electricity default rates in continental countries, such as Brazil, pose risks to the economic stability and investment capabilities of distribution utilities. This situation results in higher electricity tariffs for regular customers. From a regulatory perspective, the key issue regarding this challenge is devising incentive mechanisms that reward distribution utilities for their operational and investment choices, aiming to mitigate or decrease electricity non-payment rates and avoid tariff increases for regular customers. Despite adhering to the principles of incentive regulation, the Brazilian Electricity Regulatory Agency (ANEEL) uses a methodological approach to define regulatory targets for electricity defaults tied to econometric models developed to determine targets to combat electricity non-technical losses (NTLs). This methodology has been widely criticized by electricity distribution utilities and academics because it includes many ad hoc steps and fails to consider the components that capture the specificities and heterogeneity of distribution utilities. This study proposes a fuzzy inference-based model for defining regulatory default targets built independently of the current methodological approach adopted by ANEEL and aligned with the principles of incentive regulation. An empirical study focusing on the residential class of electricity consumption demonstrated that it is possible to adopt a specific methodology for determining regulatory default targets and that the fuzzy inference approach can meet the necessary premises to ensure that the principles of incentive regulation and the establishment of regulatory targets are consistent with the reality of each electricity distribution utility.
Full article
(This article belongs to the Section C: Energy Economics and Policy)
Open AccessArticle
An Improved Single-Phase Multiple DC Source Inverter Topology for Distributed Energy System Applications
by
Mohd Faraz Ahmad, M. Saad Bin Arif, Uvais Mustafa, Mohamed Abdelrahem, Jose Rodriguez and Shahrin Md. Ayob
Energies 2024, 17(9), 2146; https://doi.org/10.3390/en17092146 (registering DOI) - 30 Apr 2024
Abstract
This work presents an improved structure of a single-phase muti-input multilevel inverter (MIMLI) for distributed energy resources, which is capable of producing a nine-level output in symmetric mode and 21 levels in asymmetrical mode. The topology uses four DC sources and ten switches,
[...] Read more.
This work presents an improved structure of a single-phase muti-input multilevel inverter (MIMLI) for distributed energy resources, which is capable of producing a nine-level output in symmetric mode and 21 levels in asymmetrical mode. The topology uses four DC sources and ten switches, with four switches being bidirectional and the remaining unidirectional. The operation of the circuit is analyzed in an asymmetrical mode, and switching signals are accomplished using the Nearest Level Control (NLC) PWM technique. Depending on the value of the DC sources used, the number of levels can vary. In this work, different DC source algorithms were also proposed, and the analysis of the inverter has been carried out considering the algorithms producing the maximum number of levels. The inverter was simulated in MATLAB/Simulink under steady state and dynamic conditions, achieving a 3.89% THD in output. The thermal analysis was conducted using PLECS software 4.1.2 to assess losses and efficiency. A laboratory prototype of the proposed topology was developed and tested, confirming its performance through simulation results and proving it economically viable for medium- and high-power applications.
Full article
(This article belongs to the Special Issue Electro-Thermal Modeling, Aging and Lifetime Estimation of Power Electronics Circuits)
Open AccessArticle
A Method for State of Charge and State of Health Estimation of LithiumBatteries Based on an Adaptive Weighting Unscented Kalman Filter
by
Fengyuan Fang, Caiqing Ma and Yan Ji
Energies 2024, 17(9), 2145; https://doi.org/10.3390/en17092145 (registering DOI) - 30 Apr 2024
Abstract
This paper considers the estimation of SOC and SOH for lithium batteries using multi-innovation Levenberg–Marquardt and adaptive weighting unscented Kalman filter algorithms. For parameter identification, the second-order derivative of the objective function to optimize the traditional gradient descent algorithm is used. For SOC
[...] Read more.
This paper considers the estimation of SOC and SOH for lithium batteries using multi-innovation Levenberg–Marquardt and adaptive weighting unscented Kalman filter algorithms. For parameter identification, the second-order derivative of the objective function to optimize the traditional gradient descent algorithm is used. For SOC estimation, an adaptive weighting unscented Kalman filter algorithm is proposed to deal with the nonlinear update problem of the mean and covariance, which can substantially improve the estimation accuracy of the internal state of the lithium battery. Compared with fixed weights in the traditional unscented Kalman filtering algorithm, this algorithm adaptively adjusts the weights according to the state and measured values to improve the state estimation update accuracy. Finally, according to simulations, the errors of this algorithm are all lower than 1.63 %, which confirms the effectiveness of this algorithm.
Full article
(This article belongs to the Section D2: Electrochem: Batteries, Fuel Cells, Capacitors)
Open AccessArticle
Assessing the Theoretical, Minimal Intervention Potential of Floating Solar in Greece: A Policy-Oriented Planning Exercise on Lentic Water Systems of the Greek Mainland
by
Despoina Athanasiou and Dimitrios Zafirakis
Energies 2024, 17(9), 2144; https://doi.org/10.3390/en17092144 (registering DOI) - 30 Apr 2024
Abstract
According to the recent revision of the Greek National Energy and Climate Plan, the country sets out to accomplish an ambitious target concerning the integration of renewables in the local electricity mix during the ongoing decade, at the levels of 80% by 2030.
[...] Read more.
According to the recent revision of the Greek National Energy and Climate Plan, the country sets out to accomplish an ambitious target concerning the integration of renewables in the local electricity mix during the ongoing decade, at the levels of 80% by 2030. This implies the need to more than double the existing wind and PV capacity at the national level, which in turn introduces numerous challenges. Amongst them, spatial planning for new RES installations seems to be the most demanding, with the adoption of novel technological solutions in the field of RES potentially holding a key role. New technologies, like offshore wind and floating solar, are gradually gaining maturity and may offer such an alternative, challenged at the same time however by the need to entail minimum disruption for local ecosystems. To that end, we currently assess the theoretical potential of floating PVs for lentic water systems of the Greek mainland. We do so by looking into 53 different lentic water systems across the Greek territory that meet the constraint of 1 km2 minimum surface area, and we proceed with the estimation of the relevant floating PV capacity per system under the application of a minimal intervention approach, assuming PV coverage of 1% over the total lentic water system area. In this context, our findings indicate a maximum, aggregate theoretical capacity that could exceed 2 GWp at the national level, with the respective annual energy yield reaching approximately 4 TWh or, equivalently, >6% of the country’s anticipated annual electricity consumption in 2030. Finally, our results extend further, offering a regional level analysis and a set of policy directions and considerations on the development of floating solar in Greece, while also designating the energy merits of floating PVs against similar, land-based installations.
Full article
(This article belongs to the Special Issue Floating PV Systems On and Offshore)
Open AccessArticle
Study of Phase Changes in Operational Risk for Trucks
by
Andrzej Niewczas, Karol Andrzejczak, Łukasz Mórawski and Ewa Dębicka
Energies 2024, 17(9), 2143; https://doi.org/10.3390/en17092143 - 30 Apr 2024
Abstract
This study concerns the management of operational risk in truck transport using the reliability theory of risks. In this regard, the risk analysis of changes in the vehicle unavailability represents an important topic. In this study, the authors present their own method for
[...] Read more.
This study concerns the management of operational risk in truck transport using the reliability theory of risks. In this regard, the risk analysis of changes in the vehicle unavailability represents an important topic. In this study, the authors present their own method for analysing the phase changes in risk corresponding to successive sections (phases) of vehicle mileage. The presented risk analysis method is based on an integrated assessment of losses associated with the costs of incidental repairs and losses caused by lost income during vehicle downtime. This includes the following: assessment of differences in average risk and differences in the coefficient of variation in the time series of vehicle mileage phases, indicating the outliers and extremes of phase risk, identifying their physical causes and testing the statistical significance of phase risk differences. The proposed method is described mathematically and verified experimentally based on the operational data concerning trucks from two selected brands (20 trucks from each brand). We show that the method can be used to predict the continuity of transport services in the short term (one-year horizon). The method could also be useful to compare vehicles of different brands in the context of their sensitivity to operational risks.
Full article
Open AccessArticle
Modeling of Fiber Optic Strain Responses to Shear Deformation of Fractures
by
Ruwantha Ratnayake and Ahmad Ghassemi
Energies 2024, 17(9), 2142; https://doi.org/10.3390/en17092142 - 30 Apr 2024
Abstract
Identifying distributed strain sensing (DSS) patterns (or signatures), particularly those arising from different hydraulic fracture geometries, has gained significant attention and research effort. Recent works have generated a catalogue of signatures for planar hydraulic fractures in an elastic rock formation. Yet, in numerous
[...] Read more.
Identifying distributed strain sensing (DSS) patterns (or signatures), particularly those arising from different hydraulic fracture geometries, has gained significant attention and research effort. Recent works have generated a catalogue of signatures for planar hydraulic fractures in an elastic rock formation. Yet, in numerous cases (e.g., fault motion and some geothermal reservoir stimulation), the main mode of deformation is a shear on a fracture or a network of natural fractures (particularly during low pressure injection/circulation). However, the specific fiber signatures that result from such shear deformation have not been studied. In this study, we use a three-dimensional poroelastic hydraulic fracture simulator to capture the strain signatures resulting from the shear deformation of fractures in various orientations with respect to the monitoring well. Five key cases are examined: one where the fracture strike is perpendicular to the fiber, another with the strike running parallel to the fiber, a third case where the fracture strike is at 45 degrees to the fiber, a fourth case with a strike slip fault perpendicular to the fiber, and a fifth case where fiber is intersecting the fracture. Theoretically and physically meaningful results were obtained in all five cases, which completely differ from the heart-shaped signature of tensile fracture propagation. It was discovered that the strain pattern changes with the shear deformation direction with respect to the fiber. The model is then used to simulate the response of a fracture network at Utah FORGE to injection to assess whether a signature might be expected in response to the planned injection and circulation rates, and, if so, what strain pattern might be expected. The simulation confirms that a strain response can indeed be observed. More importantly, the fiber response that would be detected in the monitoring well would be a combination of strain signatures from dilation and shear deformation of differently oriented natural fractures. The results in this study provide useful insights on the application of fiber to other stimulation and/or circulation scenarios where shear deformation of a fracture or fracture network plays a major role.
Full article
(This article belongs to the Special Issue Leading the Way in Hydraulic Fracturing and Reservoir Technologies)
Open AccessReview
The Use of Renewable Energy Sources in Road Construction and Public Transport: A Review
by
Dariusz Kurz, Artur Bugała, Damian Głuchy, Leszek Kasprzyk, Jan Szymenderski, Andrzej Tomczewski and Grzegorz Trzmiel
Energies 2024, 17(9), 2141; https://doi.org/10.3390/en17092141 - 30 Apr 2024
Abstract
The development and advantages of renewable energy technologies mean that their areas of application are constantly expanding. The development of roads, transport systems, and electromobility also increases the demand for electricity. Roads occupy a certain area that could be used to install wind
[...] Read more.
The development and advantages of renewable energy technologies mean that their areas of application are constantly expanding. The development of roads, transport systems, and electromobility also increases the demand for electricity. Roads occupy a certain area that could be used to install wind turbines or photovoltaic systems that could be used to power, among others, electric vehicle charging stations and road technical infrastructure facilities (travel service areas, tunnel lighting, road signs). There are many examples around the world where such solutions have been used. This critical review of existing solutions and the possibilities of their application in new places may contribute to further development and research in this area. Particular attention was paid to the possibility of using renewable energy systems in Poland, which can be successfully transferred to other countries with a similar climate.
Full article
(This article belongs to the Section A2: Solar Energy and Photovoltaic Systems)
►▼
Show Figures
Figure 1
Open AccessArticle
Optimal PMU Placement to Enhance Observability in Transmission Networks Using ILP and Degree of Centrality
by
Muhammad Musadiq Ahmed, Muhammad Amjad, Muhammad Ali Qureshi, Muhammad Omer Khan and Zunaib Maqsood Haider
Energies 2024, 17(9), 2140; https://doi.org/10.3390/en17092140 - 30 Apr 2024
Abstract
The optimal PMU placement problem is placing the minimum number of PMUs in the network to ensure complete network observability. It is an NP-complete optimization problem. PMU placement based on cost and critical nodes is solved separately in the literature. This paper proposes
[...] Read more.
The optimal PMU placement problem is placing the minimum number of PMUs in the network to ensure complete network observability. It is an NP-complete optimization problem. PMU placement based on cost and critical nodes is solved separately in the literature. This paper proposes a novel approach, a degree of centrality in the objective function, to combine the effect of both strategies to place PMUs in the power network optimally. The contingency analysis and the effect of zero-injection buses are solved to ensure the reliability of network monitoring and attain a minimum number of PMUs. Integer linear programming is used on the IEEE 7-bus, IEEE 14-bus, IEEE 30-bus, New England 39-bus, IEEE 57-bus, and IEEE 118-bus systems to solve this problem. The results are evaluated based on two performance measures: the bus observability index (BOI) and the sum of redundancy index (SORI). On comparison, it is found that the proposed methodology has significantly improved results, i.e., a reduced number of PMUs and increased network overall observability (SORI). This methodology is more practical for implementation as it focuses on critical nodes. Along with improvement in the results, the limitations of existing indices are also discussed for future work.
Full article
(This article belongs to the Topic Solving Grid Challenges with Combined Transmission and Distribution System Models)
►▼
Show Figures
Figure 1
Open AccessArticle
Techno-Economic Evaluation on Solar-Assisted Post-Combustion CO2 Capture in Hollow Fiber Membrane Contactors
by
Junkun Mu, Jinpeng Bi, Yuexia Lv, Yancai Su, Wei Zhao, Hui Zhang, Tingting Du, Fuzhao Li and Hongyang Zhou
Energies 2024, 17(9), 2139; https://doi.org/10.3390/en17092139 - 30 Apr 2024
Abstract
In this study, a novel system which integrates solar thermal energy with membrane gas absorption technology is proposed to capture CO2 from a 580 MWe pulverized coal power plant. Technical feasibility and economic evaluation are carried out on the proposed system in
[...] Read more.
In this study, a novel system which integrates solar thermal energy with membrane gas absorption technology is proposed to capture CO2 from a 580 MWe pulverized coal power plant. Technical feasibility and economic evaluation are carried out on the proposed system in three cities with different solar resources in China. Research results show that the output capacity and net efficiency of the SOL-HFMC power plant are significantly higher than those of the reference power plant regardless of whether a TES system is applied or not. In addition, the CEI of the SOL-HFMC power plant with the TES system is 4.36 kg CO2/MWh, 4.45 kg CO2/MWh and 4.66 kg CO2/MWh lower than that of the reference power plant. The prices of the membrane, vacuum tube collector and phase change material should be reduced to achieve lower LCOE and COR values. Specifically for the SOL-HFMC power plant with the TES system, the corresponding vacuum tube collector price shall be lower than 25.70 $/m2 for Jinan, 95.20 $/m2 for Xining, and 128.70 $/m2 for Lhasa, respectively. To be more competitive than a solar-assisted ammonia-based post-combustion CO2 capture power plant, the membrane price in Jinan, Xining and Lhasa shall be reduced to 0.012 $/m, 0.015 $/m and 0.016 $/m for the sake of LCOE, and 0.03 $/m, 0.033 $/m and 0.034 $/m for the sake of COR, respectively.
Full article
(This article belongs to the Special Issue Sustainable Technologies for Decarbonising the Energy Sector)
►▼
Show Figures
Figure 1
Open AccessArticle
Numerical Investigation on the Solar Absorption Performance of Plasmonic Nanoparticles in the Focused Electric Field
by
Xueqing Zhang, Fengwu Bai, Xuesong Zhang, Tengyue Wang and Zhifeng Wang
Energies 2024, 17(9), 2138; https://doi.org/10.3390/en17092138 - 30 Apr 2024
Abstract
Planar light concentrators are potential applications for solar thermal conversion, in which the intensity of the electric field will exhibit strongly non-uniform characteristics. However, previous research has long ignored the solar absorption performance of plasmonic nanoparticles in the focused electric field. In this
[...] Read more.
Planar light concentrators are potential applications for solar thermal conversion, in which the intensity of the electric field will exhibit strongly non-uniform characteristics. However, previous research has long ignored the solar absorption performance of plasmonic nanoparticles in the focused electric field. In this work, we use the finite element method (FEM) to study the optical behaviors of a single nanoparticle and multiple nanoparticles in the focused electric field formed by vertically and inwardly imposing the initial incident light on a quarter cylindrical surface. The results show that the focused electric field can significantly improve the solar absorption abilities compared with the parallel one for all the nanoparticles due to the local near-electric field enhancement caused by the aggregation of the free electrons on the smaller zone. Further studies on the focused electric field reveal that the plasmon heating behavior of Au spheres presents a rising trend with the decrease in inter-particle spacing, as the gap is less than the radius of Au spheres. As the number of nanoparticles increases along the focal line, the absorption power of the center nanoparticles gradually tends to be stable, and it is much lower than that of a single nanoparticle. As the nanoparticles are arranged along the y and z directions, the heterogeneity of the electric field makes the optical properties uneven. Notably, the strongest electric field appears slightly close to the incident surface rather than on the focal line.
Full article
(This article belongs to the Special Issue Advanced Solar Thermal Technology)
►▼
Show Figures
Figure 1
Open AccessArticle
Biomass Higher Heating Value Estimation: A Comparative Analysis of Machine Learning Models
by
Ivan Brandić, Lato Pezo, Neven Voća and Ana Matin
Energies 2024, 17(9), 2137; https://doi.org/10.3390/en17092137 - 30 Apr 2024
Abstract
The research conducted focused on the capabilities of various non-linear and machine learning (ML) models in estimating the higher heating value (HHV) of biomass using proximate analysis data as inputs. The research was carried out to identify the most appropriate model for the
[...] Read more.
The research conducted focused on the capabilities of various non-linear and machine learning (ML) models in estimating the higher heating value (HHV) of biomass using proximate analysis data as inputs. The research was carried out to identify the most appropriate model for the estimation of HHV, which was determined by a statistical analysis of the modeling error. In this sense, artificial neural networks (ANNs), support vector machine (SVM), random forest regression (RFR), and higher-degree polynomial models were compared. After statistical analysis of the modeling error, the ANN model was found to be the most suitable for estimating the HHV biomass and showed the highest specific regression coefficient, with an R2 of 0.92. SVM (R2 = 0.81), RFR, and polynomial models (R2 = 0.84), on the other hand, also exhibit a high degree of estimation, albeit with somewhat larger modelling errors. The study conducted suggests that ANN models are best suited for the non-linear modeling of HHV of biomass, as they can generalize and search for links between input and output data that are more robust but also more complex in structure.
Full article
(This article belongs to the Special Issue Bioenergy Economics: Analysis, Modeling and Application)
►▼
Show Figures
Figure 1
Open AccessArticle
Research on Capacity Configuration for Green Power Substitution in an Isolated Grid Containing Electrolytic Aluminum
by
Min You, Yunguang Wang, Haiyun Wang, Aisikaer Wusiman and Liangnian Lv
Energies 2024, 17(9), 2136; https://doi.org/10.3390/en17092136 - 30 Apr 2024
Abstract
The deployment of a green power alternative within an isolated network, powered by renewable energy sources, in the “Three North” region of China can facilitate the substitution of high-energy-consuming industrial loads with green power. However, an inadequate power supply configuration may lead to
[...] Read more.
The deployment of a green power alternative within an isolated network, powered by renewable energy sources, in the “Three North” region of China can facilitate the substitution of high-energy-consuming industrial loads with green power. However, an inadequate power supply configuration may lead to economic and reliability issues. To address this problem, effective capacity allocation within the green power alternative isolated network is proposed. The capacity allocation process starts with the design of a network structure that aligns with local conditions. Subsequently, a capacity allocation model is developed, considering economic factors, renewable energy utilization efficiency, and system reliability. The gray wolf optimizer is enhanced to establish a capacity allocation method for the green power alternative isolated network. This method is then employed to simulate and assess the performance of the network. The results indicate that the green alternative isolated grid can successfully facilitate green power substitution, satisfying the energy requirements of the loads.
Full article
(This article belongs to the Section F: Electrical Engineering)
►▼
Show Figures
Figure 1
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, JMSE, Oceans, Remote Sensing, Water
Energy from Sea Waves
Topic Editors: Daniele Milone, Vincenzo Franzitta, Domenico Curto, Andrea GuercioDeadline: 30 April 2024
Topic in
Batteries, C, Coatings, Energies, Nanomaterials
Advances in Low-Dimensional Materials (LDMs) for Energy Conversion and Storage
Topic Editors: In Soo Kim, Jin Gu KangDeadline: 15 May 2024
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
Conferences
Special Issues
Special Issue in
Energies
Water Desalination Plants Driven by Hybrid Energy Conversion Systems
Guest Editors: Pietro Zunino, Ekaterina SokolovaDeadline: 8 May 2024
Special Issue in
Energies
Offshore Wind Support Structure Design
Guest Editor: Mehdi ShokouhianDeadline: 15 May 2024
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
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