Search Results (23,397)

With the increasing severity of environmental problems and energy scarcity, fuel cell electric vehicles (FCEVs), as a sustainable and efficient means of transportation, are attracting more attention. The ageing of fuel cells (FCs) has become an urgent problem with the development of FCEV. In order to prolong the lifetime of FCs, this paper builds a model of a vehicle driven by two power sources, FC and lithium battery (Lib) using AVL Cruise. A rule-based energy management strategy (EMS) is developed in Simulink to explore the optimal control strategy for the vehicle in terms of the durability of the FC. An FC ageing model is used to quantify the degradation voltage of different duty cycles. The results show that the FC engagement levels, OCV operations, and start/stop operations can affect the lifetime of the FC significantly. By optimising the EMS, the lifetime of the FC is improved by 9.47%. Full article

This article examines the impact of financial support mechanisms and geopolitical factors on the profitability of investments in solar power plants within Slovenia. The European Union’s energy policy prioritizes increases in renewable energy sources, aiming to reduce dependency on unstable and volatile fossil fuel markets. Solar power plants play a vital role in this transition. The energy policy framework also includes mechanisms and support systems to operate such facilities. This article analyzes electricity price trends over the past decade and addresses which support type—guaranteed purchase or operational support—has proven more profitable for investments in solar power plants up to 50 kW in Slovenia, considering economic and geopolitical influences on the electricity market. Although the global energy market has been affected by various significant events in recent years, it was found that the COVID-19 pandemic had minimal impact on the electricity market. In contrast, the onset of the conflict in Ukraine has contributed to rising electricity prices and has influenced the support dynamics essential for the development and sustainability of renewable energy systems. Analyses from the past decade indicate a higher return on investment in solar power plants when operational support mechanisms are chosen over guaranteed purchase support. Full article

Clean hydrogen (H₂) use (i.e., produced using either renewable or low-carbon energy sources) can help decarbonize energy-intensive industries, the transport sector, and the power sector. The European regulatory framework establishes that the production of green H₂ must be supported either by the electricity grid through a power purchase agreement (PPA) or by intermittent renewable energy source (RES) plants owned by the hydrogen producer. Although the issue of the optimization of hydrogen production costs has already been approached, constraints related to the current regulatory framework and the modeling of nonlinear electrolyzer efficiency still represent open problems. In this paper, a mixed-integer linear programming (MILP) problem, assuming as the objective function the overall cost minimization of the allowed energy mix for green H₂ production, is formulated. Two approaches are compared: in the first one, electrolyzers can only operate at 100% load, whereas the second one allows for more flexible electrolyzer scheduling, by enabling partial-load working operations. The simulation results of several scenarios considering different H₂ production targets, forecasted RES production, and cost for PPAs demonstrate the effectiveness of the proposed methodology. Full article

The transport sector, and especially the increase in individual vehicle ownership, contribute significantly to air pollution. The transition to electric vehicles (EVs) is seen as a sustainable alternative to reduce emissions of polluting gases. However, in Brazil, the EV market has not yet reached a significant size. Given this scenario, this study aims to analyze the factors that influence the decision to buy EVs in Brazil, highlighting personal, psychological, economic, performance, and environmental variables and barriers. The aim is also to develop a model with guidelines that can help stakeholders. The quantitative stage of the study involved a survey of 514 respondents. The data were analyzed using statistical methods, including structural equation modeling (SEM), which allowed for a deeper investigation of the proposed hypotheses. The survey findings reveal that, in the Brazilian context, performance factors—such as autonomy, availability of recharging infrastructure, and maintenance—are the main drivers influencing EV purchase decisions. Environmental factors, including energy reuse, pollution reduction, and minimizing environmental impacts, have also gained significant importance. Economic factors are crucial, particularly concerning cost–benefit perceptions. The differences between Brazil and other regions highlight the importance of accounting for cultural and economic variations when analyzing consumer behavior towards EVs. Full article

Regenerative braking energy recovery is of critical importance for electric vehicles due to their range limitations. To further enhance regenerative braking energy recovery, a dual-fuzzy regenerative braking control strategy based on braking intention recognition is proposed. Firstly, the distribution strategy for braking force is devised by considering classical curves like ideal braking force allocation and ECE regulations; secondly, taking the brake pedal opening and its opening change rate as inputs, the braking intention recognition fuzzy controller is designed for outputting braking strength. Based on the recognized braking strength, and considering the battery charging state and the speed of the vehicle as inputs, a regenerative braking duty ratio fuzzy controller is developed for regenerative braking force regulation to improve energy recovery. Furthermore, a control experiment is established to evaluate and compare the four models and their respective nine braking modes, aiming to define the dual fuzzy logic controller model. Ultimately, simulation validation is conducted using Matlab/Simulink R2019b and CRUISE 2019. The results show that the strategy in this paper has higher energy savings compared to the single fuzzy control and parallel control methods, with energy recovery improved by 26.26 kJ and 96.13 kJ under a single New European Driving Cycle (NEDC), respectively. Full article

The increasing adoption of plug-in electric vehicles (PEVs) leads to negative impacts on distribution network efficiency due to the extra load added to the system. To overcome this problem, this manuscript aims to optimally integrate distributed generators (DGs) in radial distribution networks (RDNs), while including uncoordinated charging of PEVs added to the basic daily load curve with different load models. The main objectives are minimizing the network’s daily energy losses, improving the daily voltage profile, and enhancing voltage stability considering various constraints like power balance, buses’ voltages, and line flow. These objectives are combined using weighting factors to formulate a weighted sum multi-objective function (MOF). A very recent metaheuristic approach, namely the Walrus optimization algorithm (WO), is addressed to identify the DGs’ best locations and sizes that achieve the lowest value of MOF, without violating different constraints. The proposed optimization model along with a repetitive backward/forward load flow (BFLF) method are simulated using MATLAB 2016a software. The WO-based optimization model is applied to IEEE 33-bus, 69-bus, and a real system in El-Shourok City-district number 8 (ShC-D8), Egypt. The simulation results show that the proposed optimization method significantly enhanced the performance of RDNs incorporated with PEVs in all aspects. Moreover, the proposed WO approach proved its superiority and efficiency in getting high-quality solutions for DGs’ locations and ratings, compared to other programmed algorithms. Full article

This study analyzes the thermodynamic and economic viability of modified high-temperature gas-cooled reactor (HTGR) gas-steam combined heat and power (CHP) systems compared to conventional CHP plants. The research addresses the critical need for efficient and sustainable energy production methods. Using comprehensive thermodynamic modeling and economic analysis, the study evaluates system performance under various operating conditions. Key findings reveal that modified CHP plants with HTGR and turboexpanders (TEs) demonstrate significantly higher efficiency and lower heat generation costs compared to conventional gas turbine (GT) CHP plants, despite higher initial capital investments. The modified systems achieve electricity generation efficiencies up to 48%, surpassing traditional nuclear power plants. The absence of CO₂ emissions and lower fuel costs in HTGR systems contribute to their economic advantage. This research provides novel insights into the potential of HTGR technology in CHP applications, offering a promising solution for future energy systems. The study’s originality lies in its comprehensive comparison of conventional and modified CHP systems, considering both thermodynamic and economic aspects, which has not been extensively explored in existing literature. Full article

Solar electric and solar thermal energies are often considered as part of the solution to the current energy emergency. The pipes of flat plate solar devices are normally heated by their upper surfaces giving rise to an asymmetric temperature field in the bulk of the fluid, which influences the heat transfer process. In the present work, a study of the characteristic length of tubes, or most efficient distance at which heat transfer occurs, in flat photovoltaic-thermal (PVT) hybrid solar devices has been carried out using three heat transfer fluids: water, [Emim]Ac ionic liquid and ionanofluid of graphene nanoparticles suspended in the former ionic liquid. The mean objective of the study was to know whether the heat transfer occurs in optimal conditions. Experimental measurements have been made on a commercial PVT device, and numerical simulations have been performed using the HEATT^® platform to determine the characteristic length of the process. The tests conducted showed a clear improvement in the temperature jump of the fluid inside the collector when INF is used compared to water and ionic liquid and even a higher overall energy efficiency. Electricity generation is not greatly affected by the fluid used, although it is slightly higher when water is used. Slower fluid velocities are recommended if high fluid outlet temperatures are the goal of the application, but this penalizes the overall thermal energy production. The characteristic process length is not typically achieved in parallel tube PVT collectors with ordinary flow rates, which would require a speed, and consequently, a flow rate, about 10 times lower, which penalizes the performance (up to four times), although it increases the fluid outlet temperature by 234%, which can be very interesting in certain applications. Ionanofluids may in the medium term become an alternative to water in flat plates or vacuum solar collectors for applications with temperatures close to or above 100 °C, when their costs will hopefully fall. The results and methodology developed in this work are applicable to solar thermal collectors other than PVT collectors. Full article

Here, we report the structural, optical, magnetic, and dielectric properties of La_0.67Sr_0.33Mn_1-x-yZn_xCo_yO₃ manganite with various x and y values (0.025 < x + y < 0.20). The pure and co-doped samples are called S1, S2, S3, S4, and S5, with (x + y) = 0.00, 0.025, 0.05, 0.10, and 0.20, respectively. The XRD confirmed a monoclinic structure for all the samples, such that the unit cell volume and the size of the crystallite and grain were generally decreased by increasing the co-doping content (x + y). The opposite was true for the behaviors of the porosity, the Debye temperature, and the elastic modulus. The energy gap E_g was 3.85 eV for S1, but it decreased to 3.82, 3.75, and 3.65 eV for S2, S5, and S3. Meanwhile, it increased and went to its maximum value of 3.95 eV for S4. The values of the single and dispersion energies (E_o, E_d) were 9.55 and 41.88 eV for S1, but they were decreased by co-doping. The samples exhibited paramagnetic behaviors at 300 K, but they showed ferromagnetic behaviors at 10 K. For both temperatures, the saturated magnetizations (M_s) were increased by increasing the co-doping content and they reached their maximum values of 1.27 and 15.08 (emu/g) for S4. At 300 K, the co-doping changed the magnetic material from hard to soft, but it changed from soft to hard at 10 K. In field cooling (FC), the samples showed diamagnetic regime behavior (M < 0) below 80 K, but this behavior was completely absent for zero field cooling (ZFC). In parallel, co-doping of up to 0.10 (S4) decreased the dielectric constant, AC conductivity, and effective capacitance, whereas the electric modulus, impedance, and bulk resistance were increased. The analysis of the electric modulus showed the presence of relaxation peaks for all the samples. These outcomes show a good correlation between the different properties and indicate that co-doping of up to 0.10 of Zn and Co in place of Mn in La:113 compounds is beneficial for elastic deformation, optoelectronics, Li-batteries, and spintronic devices. Full article

Electric vehicles worldwide provide numerous key advantages in the energy sector. They are advantageous over fossil fuel vehicles in many aspects: for example, they consume no fuel, are economical, and only require charging the internal batteries, which power the motor for propulsion. Thus, due to their numerous advantages, research is necessary to improve the technological aspects that can enhance electric vehicles’ overall performance and efficiency. However, electric vehicle charging stations are the key hindrance to their adoption. Charging stations will affect grid stability and may lead to altering different parameters, e.g., power losses and voltage deviation when integrated randomly into the distribution system. The distributed generation, along with charging stations with the best location and size, can be a solution that mitigates the above concerns. Metaheuristic techniques can be used to find the optimal siting and sizing of distributed generations and electric vehicle charging stations. This review provides an exhaustive review of various methods and scientific research previously undertaken to optimize the placement and dimensions of electric vehicle charging stations and distributed generation. We summarize the previous work undertaken over the last five years on the multi-objective placement of distributed generations and electric vehicle charging stations. Key areas have focused on optimization techniques, technical parameters, IEEE networks, simulation tools, distributed generation types, and objective functions. Future development trends and current research have been extensively explored, along with potential future advancement and gaps in knowledge. Therefore, at the conclusion of this review, the optimization of electric vehicle charging stations and distributed generation presents both the practical and theoretical importance of implementing metaheuristic algorithms in real-world scenarios. In the same way, their practical integration will provide the transportation system with a robust and sustainable solution. Full article

Thermochemical technologies offer potential solutions for energy recovery and mitigating the environmental impacts of biomass waste. Poultry manure (PM), a nutrient-rich biomass but also a potentially problematic biomass waste, presents an opportunity for recovery and recycling. This study compares the environmental performance of a real-scale novel gasification technology called Chimera (designed and developed through an EU LIFE program) in locally treating PM with anaerobic digestion (AD) and incineration. Using life cycle assessment (LCA), the potential environmental impacts of the technologies were assessed using the Environmental Footprint (EF) 3.0 midpoint life cycle impact assessment method. We performed an attributional LCA with substitution. The selected functional unit (FU) is the treatment of one tonne (1000 kg) PM at 40% dry matter in the Netherlands in 2021 for 20 years. The LCA results of the three technologies compared showed that no single technology outperformed the other across all the impact categories. Climate change scores for the various technologies were −383 (incineration), −206 (Chimera), and −161 (anaerobic digestion) kg CO₂ eq./FU. The results were influenced mainly by the potential utilization of the substituted heat and electricity. This study expands the existing literature on environmental sustainability assessments of PM treatment technologies. It underscores the prospects for these technologies to promote circularity while also indicating the bottlenecks for the potential environmental impacts and highlighting the most sensitive aspects that can influence the environmental performance of these technologies. Full article

Reducing the energy intensity of economies is key to meeting sustainable development goals. In the past, energy intensity has generally decreased or has shown inverted U-shape patterns. However, most global energy scenarios project unrealistically increasing relative decoupling rates of primary and final energy when compared to the observed historical trends. Here, we develop a final energy intensity decomposition which considers both productive and non-productive sectors, includes both traditional and commercial sources, and uses the exergy metric to aggregate different energy flows. We study the Portuguese economy between 1960 and 2014, a period of major energy and economic transitions. First, we find that the strong decrease of final energy intensity during the period of highest economic growth (1960–1974) is mainly driven by the following: (1) the efficiency increase in the residential sector, due to the transition from traditional sources (firewood) to electricity; (2) the relatively slow growth of energy use in the residential sector; and (3) the efficiency improvements in the productive sectors. We find that the second factor was determined by the fact that increasing per capita economic consumption was not channeled through private energy use. Second, excluding the last decade, private transportation had a growing effect on final energy intensity throughout the whole time range. Overall, we find that, essentially, remarkable technical improvements in terms of increasing final-to-useful energy efficiency made possible a relative decoupling at the final stage. Full article

Vehicular Ad Hoc Networks (VANETs) are wireless networks that improve traffic efficiency, safety, and comfort for smart vehicle users. However, with the rise of smart and electric vehicles, traditional VANETs struggle with issues like scalability, management, energy efficiency, and dynamic pricing. Software Defined Networking (SDN) can help address these challenges by centralizing network control. The integration of SDN with VANETs, forming Software Defined-based VANETs (SD-VANETs), shows promise for intelligent transportation, particularly with autonomous vehicles. Nevertheless, SD-VANETs are susceptible to cyberattacks, especially Distributed Denial of Service (DDoS) attacks, making cybersecurity a crucial consideration for their future development. This study proposes a security system that incorporates a hybrid artificial intelligence model to detect DDoS attacks targeting the SDN controller in SD-VANET architecture. The proposed system is designed to operate as a module within the SDN controller, enabling the detection of DDoS attacks. The proposed attack detection methodology involves the collection of network traffic data, data processing, and the classification of these data. This methodology is based on a hybrid artificial intelligence model that combines a one-dimensional Convolutional Neural Network (1D-CNN) and Decision Tree models. According to experimental results, the proposed attack detection system identified that approximately 90% of the traffic in the SD-VANET network under DDoS attack consisted of malicious DDoS traffic flows. These results demonstrate that the proposed security system provides a promising solution for detecting DDoS attacks targeting the SD-VANET architecture. Full article

Triboelectric nanogenerators (TENGs) are a promising technique for harvesting environmental energy that is based on electrostatic induction and contact electrification. This is a method that uses every relative motion between two electrodes to convert mechanical energy into electrical energy. Several modes of TENGs are designed based on various relative motions between electrode pairs. As TENGs are a surface phenomenon, properties such as the structure of the electrodes are key parameters that affect their performance. In this paper, in order to identify the best pattern designed adapted to the TENG mode, the effect of surface structures in each mode is investigated numerically. To achieve the best performance of the micro-patterned electrode, a comparative study has been conducted on the four TENG modes under the same conditions. To reach this goal, micro-patterned shapes such as pyramid, spherical, and cube structures are designed, and the open circuit voltage is calculated and compared to a flat surface. The results show that surface modification has a significant role in TENG’s performance. Based on this study, by using a cube-patterned electrode instead of a flat electrode, the output voltage increases from 233 V to 384 V in sliding mode. Also, by applying the spherical pattern, the output voltage is 1.7 times higher than a flat electrode in contact-separation mode. In the case of investigating TENG pattern structure, the results show that the electrical outputs of the patterned layer depend on the mode. The spherical pattern has a higher impact in contact-separation mode compared to the cube pattern. Meanwhile, in sliding mode, the cube pattern has a greater effect. This work provides a hint for designing an effective pattern on electrodes for a particular mode to enhance TENG performance. Full article

Photovoltaic (PV) and wind energy generation result in low greenhouse gas footprints and can supply electricity to the grid or generate hydrogen for various applications, including seasonal energy storage. Designing integrated wind–PV–electrolyzer underground hydrogen storage (UHS) projects is complex due to the interactions between components. Additionally, the capacities of PV and wind relative to the electrolyzer capacity and fluctuating electricity prices must be considered in the project design. To address these challenges, process modelling was applied using cost components and parameters from a project in Austria. The hydrogen storage part was derived from an Austrian hydrocarbon gas field considered for UHS. The results highlight the impact of the renewable energy source (RES) sizing relative to the electrolyzer capacity, the influence of different wind-to-PV ratios, and the benefits of selling electricity and hydrogen. For the case study, the levelized cost of hydrogen (LCOH) is EUR 6.26/kg for a RES-to-electrolyzer capacity ratio of 0.88. Oversizing reduces the LCOH to 2.61 €/kg when including electricity sales revenues, or EUR 4.40/kg when excluding them. Introducing annually fluctuating electricity prices linked to RES generation results in an optimal RES-to-electrolyzer capacity ratio. The RES-to-electrolyzer capacity can be dynamically adjusted in response to market developments. UHS provides seasonal energy storage in areas with mismatches between RES production and consumption. The main cost components are compression, gas conditioning, wells, and cushion gas. For the Austrian project, the levelized cost of underground hydrogen storage (LCHS) is 0.80 €/kg, with facilities contributing EUR 0.33/kg, wells EUR 0.09/kg, cushion gas EUR 0.23/kg, and OPEX EUR 0.16/kg. Overall, the analysis demonstrates the feasibility of integrated RES–hydrogen generation-seasonal energy storage projects in regions like Austria, with systems that can be dynamically adjusted to market conditions. Full article