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Developing cost-effective and stable materials for the electrocatalysis of hydrogen evolution reaction (HER) remains challenging. In this study, efficient catalysts for HER were synthesized by integrating the cobalt and molybdenum oxides via electrodeposition, followed by subsequent sulfurization of the as-prepared oxides using chemical vapor deposition (CVD). This methodology allowed the incorporation of both cobalt and molybdenum components into the catalyst in a single step. The as-synthesized CoSx@MoSx/MoOx-based catalysts exhibited excellent hydrogen production performance in acidic media owing to the presence of Co-S and Mo-S bonds in the hybrid structure. Particularly, CoSx@MoSx/MoOx(90@360) and MoSx@CoOx(180@180) displayed the best HER performances with low overpotentials of 80 mV and 150 mV, respectively. The catalysts were highly stable, with their stability preserved for over 1000 cycles with marginal reduction in overall efficiency. Therefore, these findings suggest the potential of CoSx@MoSx/MoOx and MoSx@CoOx composites as ideal candidates for developing low-cost catalysts for electrochemical hydrogen production. [ABSTRACT FROM AUTHOR]

Integrating more active components into a catalyst material could facilitate the development of multifunctional electrocatalysts for energy conversion and storage applications. In this study, we developed a multifunctional electrocatalyst, namely, Pd alloyed with Co-Fe deposited on N-doped mesoporous carbon derived from tissue paper (Pd@Co-Fe/N-TDC). The synergism in Pd@Co-Fe/N-TDC, stemming from the interatomic alloy between Pd and Co-Fe, N-doped mesoporous carbon with defective surfaces, distribution of polyhedral Pd nanoparticles, and strong metal-support interfacial interaction, resulted in significantly high electrocatalytic performance for both oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). Pd@Co-Fe/N-TDC was found to be an efficient bifunctional oxygen electrocatalyst, and this was evidenced by a high onset potential (1.01 V) and kinetic current density (2.6 mA/cm2) for the ORR and by a low overpotential (296 mV) and a low Tafel slope value (38 mV/dec) for the OER, along with a small Δ E of 736 mV. The catalyst also exhibited high durability for both ORR and OER, even after 10000 and 5000 cycles, respectively. Theoretical assessment provides an insight into the synergism of active metal sites in Pd@Co-Fe/N-TDC, which showed its potential for use as a non-Pt electrocatalyst for energy applications. [ABSTRACT FROM AUTHOR]

Summary: In the pulp and paper industry, black liquor, which is a biomass resource, is burned to produce electricity. Black liquor is concentrated to 21 wt% water through an evaporator before being burned in a boiler. For the evaporator, a multiple‐effect evaporator (MEE) is mainly used, but it requires a large amount of energy and cost. Therefore, it is crucial to reduce energy and cost of evaporation process. Hence, this study suggested a novel process model that integrated mechanical vapor recompression (MVR) with MEE to increase the energy efficiency. The suggested MVR‐assisted evaporation process was composed of preheating and evaporation processes to effectively concentrate black liquor. In addition, it reduced the steam consumption of MEE by using MVR, which uses relatively inexpensive electric energy in the pre‐evaporation process. In the simulation results, the steam, electricity consumption, and the latent heat recovered from the secondary vapor of the suggested process were quantitatively analyzed to verify the energy efficiency. The results indicate that the proposed process increases substantial energy efficiency compared to the conventional process. Then, the appropriateness of the suggested process was evaluated by the techno‐economic analysis. The total annualized cost (TAC) is determined for both current and potential future economic benefits. TAC of the MVR‐assisted MEE configuration can be reduced by up to 77.54%. [ABSTRACT FROM AUTHOR]

Summary: Microfluidic fuel cell (MFC) stacking is a prerequisite to enhance its power output for practical applications. However, most MFC stacks reported in the present literature require external pumps to maintain the co‐laminar flow and complex fluidic management networks for homogeneous flow and reactant distributions. To address these issues, a novel paper‐based self‐pumping MFC stack with potassium formate as the fuel and hydrogen peroxide as the oxidant is proposed in this study. The capillary action is employed to achieve passive liquid flow. A vertical stack structure with the unit cells piled one above another compactly is adopted to reduce the volumetric costs. The experimental results show that the maximum power outputs of the two‐cell and three‐cell stack prototypes are 4.01 and 7.26 mW cm−2, outperforming the MFC unit by 5.81 and 10.52 times, respectively. The superior performance is attributed to its distinct vertical stacking structure, which brings the enhanced capillary flows in the paper wicks and reduced ohmic losses in comparison with the unit cell. Further, effects of the filter paper and reactant concentrations on the stack performance were examined, and mass transfer of the fuel and/or oxidant to the electrode/electrolyte interface was identified as the main limiting factor. A loose microstructure of the paper wick was found beneficial in enhancing the mass transfer. The potential applications of the MFC stack in a variety of portable electronics are broad. [ABSTRACT FROM AUTHOR]

Summary: A novel bioprocess design to convert paper mill sludge (PMS) to biofuels is proposed in this work. The design utilizes cellulosic fiber recovered from the PMS via optimized de‐ashing (HCl washing) step. This work specifically provided a technical and economic analysis of paper mill sludge conversion into biofuel production using a novel protocol. The protocol is based on scanning electron microscopy (SEM) analysis to assess the quality of the contained cellulose prior to further processing. The results are crucially important to determine the suitability of the PMS feedstock to produce biofuels. SEM analysis was employed as a preliminary screening tool to evaluate sludge digestibility and conversion. The SEM characterization technique established a direct relationship between the fiber morphology, presence of crystals salts and sugar yield after enzymatic hydrolysis. Substantial structural changes were observed before and after de‐ashing the sludge samples, leading to a correlation between the surface morphology and the washing step. The results suggested that de‐ashing changes the surface morphology and upon analysis, increased the sugar yield up to about 86% as opposed to 2.2% in sludge sample A as an example. The PMS conversion into biofuel was simulated using Aspen PLUS and compared to a similar process using corn stover as feedstock. The simulation results showed it is 20% cheaper to produce bioethanol from PMS compared to corn stover. The simulation revealed less energy demand by around 13 320 MJ/h compared to that when corn stover was used. [ABSTRACT FROM AUTHOR]

Summary The development of an efficient water electrolyser is essential for sustainable hydrogen production; however, its application remains limited by the insufficient performance of the electrode. Herein, we report a rapid, simple, and cost‐effective fabrication of an Ni‐Co‐S cathode for the hydrogen evolution reaction (HER), which is directly usable for an anion exchange membrane water electrolyser (AEMWE). The Ni‐Co‐S electrocatalysts are prepared on a carbon paper (CP) substrate by a one‐step electrodeposition method by controlling deposition parameters such as the deposition potential, time, and electrolyte composition. The optimized Ni‐Co‐S/CP electrode demonstrates a high HER activity with an overpotential of 91 mV at −10 mA/cm2 in 1.0 M KOH. An AEMWE single cell employing the Ni‐Co‐S/CP cathode coupled with a commercial IrO2/CP anode exhibits a current density of 1.7 A/cm2 at 2.4 Vcell, which is higher than that of an AEMWE single cell with a commercial Pt/C/CP cathode; this is attributable to the enhancement of the electron and reactant/product transfer via appropriate cathode design. [ABSTRACT FROM AUTHOR]

Summary: Direct liquid fuel cell (DLFC) and membraneless fuel cell using the anode consisting of buckypaper (BP) and vitamin B12 (Vit B12) (BP/Vit B12) is introduced in physiological condition, while vitamin C (Vit C) is used as anodic fuel. Due to the high sensitivity of Vit B12 and the inherent feature of BP, the onset potential for the oxidation reaction of Vit C catalyzed by BP/Vit B12 is −0.1 V (vs Ag/AgCl), and its anodic current density measured at 0.3 V (vs Ag/AgCl) is 1.82 mA cm−2 even in a low Vit C concentration (10 mM). Regarding performance in fuel cells, maximum power density (MPD) of Vit C fuel cell containing membrane and Pt‐based air cathode is 0.62 ± 0.067 mW cm−2 in 0.01 M Vit C, and this is 3.1 times higher than that of fuel cell containing pristine BP. In addition, in a paper‐based flexible membraneless fuel cell using BP/bilirubin oxidase as cathode and the concentration of cerebrospinal fluid within the human body (0.35 mM Vit C), its MPD is 57.7 ± 4.02 μW cm−2. This means this suggested Vit C fuel cell system can replace the conventional primary batteries considered as the power source of implantable sensors and stimulation devices to treat neurological disorders. [ABSTRACT FROM AUTHOR]

Summary: Tremendous research has focused on the wearable electronic device, leading to the basic requirement of suitable power sources. Herein, we report one bendable paper‐based zinc‐air battery with a novel hollow channel structure. It achieves a maximum power density of 138 mW/cm2, outperforming the state‐of‐art paper‐based batteries reported previously. The boosted performance is assigned to the low charge transfer resistance and facilitated mass transfer from the hollow structure. It demonstrates the positive design of microchannel structure is profitable for the power‐generation enhancement, and offers a possible route to commercialize the paper‐based power generators. [ABSTRACT FROM AUTHOR]

Summary: This work describes a two‐step method of in situ electrodeposition and following oxidation to prepare carbon paper (CP) modified with tin dioxide (SnO2) particle as bifunctional electrode for vanadium redox flow battery. Electrodeposition technique was employed to load metal tin particle on CP, which was subsequently oxidized to tin dioxide at high temperature. CPs modified by SnO2 with different content (CP/SnO2‐1, CP/SnO2‐2, and CP/SnO2‐3) were obtained by controlling electrodeposition time. CP/SnO2 presents an increase in electrochemical performance including faster charge and mass transfer compared with pristine CP. Among all samples, CP/SnO2‐2 with proper decorated SnO2 exhibits superior electrocatalytic performances for V3+/V2+ and VO2+/VO2+ reactions. Raised performances can be attributed to that SnO2 nanoparticles provide more active sites leading to rapid electrochemical kinetic of vanadium redox reactions. In addition, mass transfer can be accelerated due to the excellent hydrophilicity of SnO2. The cell using CP/SnO2‐2 as bifunctional electrode exhibits better stability and higher capacity retention during 50‐cycle charge‐discharge test. The cell for CP/SnO2‐2 shows higher energy and voltage efficiency, suggesting that introduction of SnO2 can decrease electrochemical polarization. At 150 mA cm−2, energy efficiency of the cell increases by 7.8% through using CP/SnO2‐2. [ABSTRACT FROM AUTHOR]

Summary: This article proposes a methodology based on artificial intelligence to enhance methane production from waste paper. The proposed methodology combines fuzzy logic‐based modelling and modern optimization. Firstly, a robust Adaptive Network‐based Fuzzy Inference System model of methane production process through fuzzy logic modelling is created using experimental datasets. Second, a particle swarm optimizer was used to obtain the optimal process conditions. During the optimization procedure, the beating time and feedstock/inoculum ratio are employed as decision variables in order to maximize methane production. The obtained resulted from the proposed methodology are compared with those obtained by response surface methodology. The results of the comparison confirmed the superiority of the proposed methodology. The fuzzy model shows a better fitting to the experimental data compared to ANOVA. The fuzzy model showed a higher coefficient of determination and a lower value of root mean squared errors compared to ANOVA. Moreover, the proposed strategy, that is, modelling and optimization, is an effective method for increasing the biomethane yield at extended range conditions. [ABSTRACT FROM AUTHOR]

Summary: It is well recognized that combining nonpotable water with solar energy to desalinate water and produce water vapor is an effective route to solve the shortage of fresh water. However, the solar vapor generation suffers from either low solar energy efficiency or complex and high‐cost devices. Herein, we explore a black membrane based on polypyrrole (PPy) and filter paper to enhance solar‐to‐vapor conversion performance, thus providing a low‐cost, stable, and strong efficient solar vapor generator. This device displays high solar‐to‐vapor conversion efficiencies of up to approximately 92.2% and 95.6% under irradiation of 1 and 4 kW m−2, respectively. Therefore, this paper‐based high solar‐to‐vapor conversion and scalable evaporator provides a promising solution to the problem of freshwater scarcity and nonrenewable recourses. [ABSTRACT FROM AUTHOR]

Summary: Paper microfluidic devices are innovative platforms for building miniaturized devices for energy harvesting, energy storage, and sensing applications. Such devices are reported to be used as membraneless microfluidic fuel cells to power portable electronic in a pump‐less manner by leveraging the embedded capillaries and co‐laminar flow. This paper demonstrates fabrication and characterization of the high‐performance metal‐free aluminum‐air microfluidic paper fuel cell (AAMPFC). Herein, aluminum foil acts as an anode, buckypaper with built‐in multiwalled carbon nanotubes (MWCNTs) acts as a cathode and sodium hydroxide (NaOH) works as an electrolyte. The novel AAMPFC is analyzed with various electrolyte concentrations, and maximum output voltage, current density, and power density are recorded. This easy‐to‐fabricate AAMPFC platform, costing less than US$ 0.5, is further optimized to achieve peak energies by stacking four AAMPFCs (in series and parallel) with various concentrations of electrolyte (NaOH). With parallel configuration, maximum open‐circuit potential (OCP), peak current (mA/cm2), and power density (mW/cm2) of 1.32 V, 50.67 mA/cm2 and 22.80 mW/cm2, respectively, are observed with optimized electrolyte, while with series stacked configuration, a stable OCP of 4.10 V is measured. In a series configuration, AAMPFC generated sufficient power to powering a scientific calculator with LCD display for 3 days and 11 LEDs for 10 hours continuously. This research work provides a significant method to enhance the output power with inexpensive parameters (buckypaper, single paper microchannel) to power portable electronic devices. Further, the performance can be enhanced by investigating AAMPFC with various grades of aluminum foil in combination with different grades of porous cellulose papers. [ABSTRACT FROM AUTHOR]

Summary: Porous conducting carbon fiber‐based composite paper is used as an electrode backing in the fuel cell assembly. It not only acts as a channel through which the reactant and product gases pass to and from the bipolar plate and the catalyst site but also helps in the flow of electrons. In order to perform its role efficiently, it should have sufficient strength, high electrical conductivity, and ideal porous structure. Carbon paper has been fabricated, which builds up the required composite properties. Studies have been conducted to optimize the fiber/matrix ratio in the carbon paper, while ensuring the perfect combination of porosity, mechanical strength, and electrical conductivity for an electrode in a proton electrolyte membrane fuel cells. Detail physico‐mechanical and electrochemical characterizations further ascertain that the fiber/matrix ratio plays an important role in tuning the composite properties. The polarization curve of the unit proton exchange membrane (PEM) fuel cell (with an effective electrode area 4 cm2) shows a peak power density of 916 mW/cm2 for the sample with fiber/matrix ratio of 65:35, which is almost the same as the commercially available sigracet gas diffusion layer (SGL) carbon paper tested under similar conditions. Further, proportionally enlarging the electrode area to 100 cm2 shows that the carbon paper not only shows almost repeatable results in a given set up but also scales up. [ABSTRACT FROM AUTHOR]

Summary: Miniaturization of devices, combined with other features such as portability, proneness to automation, rapid performance, amenability to integration, multiplexing, and cost‐effectiveness, is rapidly increasing for various sensing and energy harvesting applications. One such emerging area is the development of microfluidic fuel cell on cellulose papers, which has enormous scope to optimize its performance. This is primarily because such devices eliminate the need for membranes as well as external pumps since they have built‐in colaminar flow embedded capillaries. Such peripherals are usually used in conventional microfluidic fuel cells, which are fabricated using methods like photolithography, PDMS lithography, and 3D printing. This paper presents investigations on microfluidic paper–based fuel cells (MPFCs) with different cellulose absorbent pads for their performance optimization. Herein, the MPFC utilizes formic acid as fuel, oxygen from quiescent air as oxidant, and sulfuric acid as electrolyte for conducting ionic exchange under colaminar flow. The electrodes are realized through simple pencil strokes depositing a thin layer of graphite. The porous graphite electrodes act as diffusion agents breathing oxygen directly from the atmospheric air. Such an MPFC configuration, costing less than US $1, was optimized to achieve maximum energy density by examining various combinations of absorbent pads with different grades of cellulose papers. It is seen that the maximum open circuit potential is 0.46 V, while the maximum current and power densities are 1505.66 μAcm−2 and 173.97 μWcm−2, respectively, with a grade 6 absorbent pad. Such performance can be further enhanced by investigating MPFCs with various graphite pencils with a diverse number of strokes at different concentration levels. [ABSTRACT FROM AUTHOR]

Summary: Coronavirus disease (COVID‐19) has spread all across the world. Low‐ and medium‐income countries are more affected economically and socially compared to developed countries due to the lack of a rapid, robust, and affordable testing infrastructure. Furthermore, the high cost of real‐time polymerase chain reaction (PCR) system, sophisticated user‐handling procedure, and high expense of the conventional clinical tests are the root causes of the less accessibility of the testing systems to the users. In this study, a COVID‐19 Point‐of‐Care (POC) ecosystem model is proposed for the low‐ and medium‐income countries (or energy deprived countries) that will facilitate the technological development with locally available fabrication components. In addition, the nontechnological development phases have also been discussed, which encompasses the collaboration among academia, local as well as government bodies, and entrepreneurial ventures. In addition, a hypothetical design of a microfluidic paper‐based analytical (μPADs) POC platform is proposed to detect COVID‐19 analyte using unprocessed patient‐derived saliva, which is a miniaturized form‐factor of conventional real‐time polymerase chain reaction (PCR) technique. The device contains four major reaction zones, which are sample zone, buffer zone, loop‐mediated isothermal amplification (LAMP) Master Mix zone, Ethylenediamine tetraacetic acid (EDTA) zone, and sensor zone. To obtain quicker test results and easier operation, a handheld image acquisition technique is introduced in this study. It is hypothesized that in a remote setting, the proposed design could be used as an initial guideline to develop a POC COVID‐19 testing system, which may be simple, easy‐to‐use, and cost‐effective. [ABSTRACT FROM AUTHOR]

Summary: Perovskite solar cells are one of the most promising photovoltaic technology, presenting the fastest power conversion efficiency (PCE) growth from 3.8 % to 24.2 % in just 10 years. However, there are still challenges hindering its commercialization such as the expensive back‐contact made of gold. Carbon‐based materials, mainly carbon pastes made of carbon black and graphite, have already proven to be good candidates as back‐contacts because of their features such as low cost, high conductivity, and high stability. In this work, the replacement of gold back‐contact by a carbon paper with a microporous layer coated with a PEDOT:PSS dispersion is reported. To the best of the author's knowledge, this material has never been reported for perovskite solar cells. A PCE of 9.22 % was obtained, representing 62 % of the PCE obtained for the same cell but with a gold back‐contact. [ABSTRACT FROM AUTHOR]

The increasing environmental consideration and the growth of instability of the energy market call for methods that can process the organic fraction of municipal solid waste (OFMSW) into fuel instead of disposal. Due to the pyrolysis and gasification that are efficient procedures to achieve valuable products, gasification of OFMSW with different particle sizes and compositions was carried out in the presence of Ni and Ni-Ce-loaded Y-zeolite in a multizone tubular kiln reactor. During the experiments, 500°C was applied in the first reactor zone, while the 2nd zone was at an elevated temperature of 600°C or 900°C in the presence of steam. The combined pyrolysis and gasification experiments were also carried out without a catalyst with the same operating conditions. The feedstock was collected from the organic fraction of a Hungarian mechanical-biological treatment (MBT) plant and was separated into four different fractions based on particle size: <1 cm dry biomass and fine particles, 1-2 cm paper-rich, 2-6 cm paper and plastic-rich feedstocks, and <6 cm mixture of these fractions. During the experimental work, product yields; gaseous product composition; the ratio of H2/CO, CO2/CO, and CH4/CO; and lower heating value were determined in the function of feedstock composition, the applied temperature, and catalysts. It was found that the hydrogen content and H2/CO ratio of gaseous products were increased due to catalyst application and temperature elevation in the 2nd reactor zone. The addition of Ce to the Ni/Y-zeolite catalyst was advantageous in the case of hydrogen formation at a lower temperature (600°C). The hydrogen and methane content of products obtained from the catalytic pyrolysis-gasification of paper and plastic-rich OFMSWs on elevated temperatures were higher, which increased the lower heating value of those products. Based on the elemental analysis of the obtained solid residues, it was found that paper/plastic-rich feedstock released hydrogen and carbon with a higher extent. 1-2 cm feedstock-related solid residues had the highest H/C ratio which caused a 12.5-12.8 MJ/kg gross heating value. As a result, combined pyrolysis and gasification appear to be an efficient method to attain valuable outputs from OFMSW not only in gas but also in solid products. [ABSTRACT FROM AUTHOR]

Optimal sizing and management of hybrid wind turbine-diesel-battery system for reverse osmosis seawater desalination in NEOM city is the objective of the paper. Therefore, the paper explored the different factors to optimize and introduce a technoeconomic evaluation and energy management of a stand-alone wind turbine (WT) system, diesel generator (DG), and battery storage (BS). The suggested WT/DG/BS system is implemented to feed seawater reverse osmosis (SWRO) unit in NEOM. The necessitated desalinated water per day is 100 m3. To determine the optimal size of WT/DG/BS corresponding to the minimum cost of energy (COE) and net present cost, two different ratings of the SWRO units (SWRO-100 and SWRO-150), three control dispatch strategies (load following, cycle charging, and combined dispatch), and five types of batteries are considered. HOMER software is performed to simulate and optimize the WT/DG/BS. The optimization results indicated that the best battery storage is the Trojan SAGM battery. In this case, the COE ranged between $0.337/kWh and $0.564/kWh. The lowest COE of $0.377/kWh is obtained when using a combined control strategy and SWRO-100 unit, whereas the worst COE of $0.564/kWh is obtained when using load following control strategy and SWRO-150 unit. The best option of the WT/DG/BS system to supply the SWRO unit is option number 26. This system includes one wind turbine of 90 kW, DG of 25 kW, 47 Trojan SAGM batteries, a 23.8 kW converter, a SWRO-100 unit, and a combined control strategy. The net present cost and the initial cost are $950,725 and $221,495, respectively. The annual operating cost and annual consumed fuel are $56,409 and 36,396 L, respectively. Compared with using only a 25 kW diesel generator, the COE reduced from $0.373/kWh (using only DG/BS) to $0.337/kWh (using the best option) by around 9.65%. Under this condition, the values for the internal rate of return, return on investment, and simple payback are 11%, 7.8%, and 8.3 years, respectively. [ABSTRACT FROM AUTHOR]

Nowadays, most of the works are based on electric vehicle usage for sustainable transportation using traditional energy storage device, such as battery. Usage of batteries in electric vehicles is having several disadvantages, for example, life span, temperature, and charge estimation. In this paper, a novel control scheme for battery and supercapacitor- (SC-) based hybrid energy storage system (HESS) using hybrid proportional and integral- (PI-) sliding mode control (SMC) for electric vehicle (EV) applications is introduced and implemented. This HESS with hybrid controller proves the usage of batteries in EVs to its fullest potential. The conventional control strategy for HESS follows two-loop voltage and current PI controllers with low-pass filter (LPF) and involves tuning of multiple control parameters with variations of source and load disturbances. Performance of the system is affected by tuning PI controller constants. A slow response time with linear PI controllers is long which is not advisable for starting and sudden jerk conditions of EVs. Moreover, the PI controller performance is affected by the system parameter variations during load changes. And these parameters are dynamic in nature due to nonideal conditions. In this paper, a hybrid PI-sliding mode controller (SMC) scheme is designed to control the bidirectional DC-DC converters to overcome the drawbacks of aforementioned issues. The combined PI-SMC controller reduces the tuning effort and reduces the effect of shift in operating point in controller performance. Linear modeling is done using small signal analysis for each subsystems. Permanent magnet synchronous machine (PMSM) is used as electric vehicle. The entire system and its controllers are simulated using MATLAB-Simulink, and detailed comparison is carried between conventional PI and proposed hybrid PI-SMC scheme to regulate the DC link voltage. The results are tabulated and show that the hybrid PI-SMC scheme outperforms in transient and steady-state conditions than the traditional PI controller. A scaled hardware prototype of 48 W set-up is developed using dSPACE-1104, and the experimental results have been carried out to verify the proposed system's feasibility. [ABSTRACT FROM AUTHOR]

This paper is aimed at performing a comprehensive review of the approaches employed in nanosatellite platforms, specifically 1 U and 3 U, for electrical power systems (EPS). Moreover, it seeks to develop a robust maximum power point tracking (MPPT) controller using the sliding mode control (SMC) method. The proposed control strategy is intended to monitor the solar panel's maximum power point (MPP) and adapt to changes in temperatures and solar irradiance in low Earth orbit (LEO). The EPS model, designed with the proposed sizing method, is built in MATLAB-Simulink and integrates a solar panel, battery storage, and power converters controlled by diverse MPPT methods. Then, simulation results demonstrate the effectiveness of the proposed SMC approach compared to other conventional control methods for the designed EPS under varying LEO conditions. To achieve a robust validation of the most appropriate MPPT control method under steady-state conditions, this paper presents an experimental investigation into the proposed EPS hardware design. The proposed SMC method achieved an increase in power generation from 10% to 12% for buck and boost power converters, respectively, compared to traditional control methods. [ABSTRACT FROM AUTHOR]

This paper introduces a novel concept of a TRISO-fueled salt-cooled reactor (TFSCR). The core contains circulating pipes filled with molten salt carrying TRISO particles. The reactor achieves online refueling by slowly circulating the molten salt through the pipeline. The reactor utilizes the same molten salt as the coolant and graphite as the moderator. The reactor design has the characteristics of safety, economy, and nonproliferation. TRISO particles exhibit greater resistance to neutron irradiation, corrosion, oxidation, and high temperatures compared to conventional fuels. A molten salt-cooled reactor can also operate at higher temperatures, consequently enhancing power generation efficiency. Furthermore, lower operating pressures can mitigate the risk of significant damages and loss of coolant caused by accidents, thereby enhancing reactor safety. This paper presents the basic nuclear design of TFSCR under the assumptions concerning the average fuel power density, the volumetric core power density, and the core temperature. At the same time, the feasibility of online refueling and long-life operation was evaluated by fuel burnup calculation. [ABSTRACT FROM AUTHOR]

This paper presents a performance analysis and optimization of heat exchanger fin shapes in a thermoelectric power generation system for ship waste heat recovery. It proposes a new curved fin design aimed at enhancing heat transfer efficiency and maximizing thermoelectric power generation capacity. Numerical analysis and response surface methodology (RSM) focused on 225 parameters to identify the optimal fin shape. Computational analysis using CFX was conducted on the thermoelectric module system with curved fins. The methodology was verified by comparing and analyzing CFD and PIV experimental results for a curved fin. The paper comprehensively compares the fluid dynamics of curved fins and straight fins, highlighting how curved fins improve heat exchange by creating a tip leak vortex. The results demonstrate the superiority of the curved fin design in terms of heat transfer efficiency and net power generation over the conventional straight fin design. [ABSTRACT FROM AUTHOR]

In recent years, the proportion of wind power in new energy generation has gradually increased. The natural wind in wind farms is subject to velocity attenuation by the wake effect, so improving the efficiency of wind farm power generation has become a problem that must be solved for wind power generation. Considering the uncertainty of wind farms, we regard wind farm layout optimization (WFLO) as a strongly nonlinear problem. In this paper, we improve the sparrow search algorithm (SSA) using dynamic opposite learning (DOL) strategy. Twenty-eight benchmark test results prove that compared with other algorithms, the improved algorithm DOLSSA has excellent robustness and the ability of searching for a better solution when solving a strongly nonlinear optimization problem, and the DOL strategy effectively improves the shortcomings of the original algorithm which is prone to local optimization and space limitation. In this paper, the authors establish the dynamic rotational coordinates of wind farms and set six different physical scenarios by considering the wind direction and wind speed variables, and the results prove that the performance of DOLSSA is optimal. [ABSTRACT FROM AUTHOR]

Why Hydrogen. Nowadays, the energy industry and research laboratories are heavily working on developing ideas and methods to reduce and/or eliminate the carbon dioxide emission to control the problem of global warming. The solution relies on finding alternative green energy resources to reduce the world's dependence on conventional fossil hydrocarbon energy. Green hydrogen gas from water stands on the top of the alternative resources since it does not produce carbon dioxide when burned and in return does not add to global warming. Since seawater is the largest resource on earth, this makes the hydrogen production from seawater the most economically attractive solution. It is very important to avoid using fresh water as a source of hydrogen energy due to the dependence of all living creatures, humans, animals, plants, etc., on such very limited resources. In this paper, the applications of the proposed novel solution of green hydrogen production directly from seawater relies on solving one of the major problems, electrode corrosion. Generating Hydrogen. The direct method to produce green hydrogen from seawater is the electrolysis technique. This technique requires a direct current power supply for the positive and the negative electrodes. The outcome of the electrolysis is decomposing the saltwater to its positively charged hydrogen and sodium ions at the negative electrode and its negatively charged oxygen and chlorine ions at the positive electrode. The Real Challenge. Traditionally in the electrolysis analysis of water, both electrodes are made of metals. At the positive electrode, both the oxygen and the chlorine cause a high rate of corrosion to that electrode. This results in the interruption of the electrolysis process, bad water condition due to the corrosion deposits, and cost burden due to the need to periodically replace the corroded electrodes and/or use high-cost corrosion-resistant alloys. The Novel Solution. A low-cost but powerful solution to the corrosion problem is introduced, tested, and experimentally proved. The novelty of the solution relies on replacing the classic special high-cost metallic positive electrode with a nonmetallic, no-cost, one. The nonmetallic electrode is made of surface rock portions that have high porosity and pore volume and high permeability and pore connectivity and is saturated with saline water. Surface rocks with the above properties exhibit very low resistivity and hence conduct electricity like metallic electrodes. The voltage and the current conducted by such electrode are controlled by the electrode geometry, connectivity, and physical properties. Results and Discussions. Multiple experiments using the proposed nonmetallic high-porosity and high-permeability positive electrode are conducted and presented in this paper. The experimental work is based on testing multiple rock electrodes with different rock properties, sizes, and connectivity in comparison to the metallic ones. The comparison showed that the novel solution solved the corrosion challenges of the metallic electrodes with excellent efficiency. [ABSTRACT FROM AUTHOR]

The bioeconomy model provides an alternative view of global economic systems by putting sustainable practices combined with digital approaches at the forefront to tackle issues such as climate change. To address this new business trends, financial institutions began to set up the environmental, social, and governance (ESG) business units to evaluate their business strategies. This paper is aimed at examining the nonfinancial effect created by the digital transformation (DT) activities, highlighting the role of enterprise heterogeneity after the implementation of Environmental Protection Law (EPL) in China. We employ the panel data of A-share listed companies from 2010 to 2020, selecting DT and ESG indicators as the important representations of "Industry 5.0." Our empirical results demonstrate a positive impact of EPL on the ESG performance in sight of resource enterprises (REs), environmental enterprises (EEs), and polluting enterprises (PEs), but a negative impact of EPL on the DT indicators among those environmental related industries. Additional causal relationship regression reveals that enterprise DT has an intrinsic promoting effect on the ESG performance, emphasizing on the high risk of digitization process being the shock transmitters to enterprise nonfinancial indices. Notably, the connectedness of environmental policy illustrates dynamic patterns by parallel trend test and propensity score matching (PSM) DID regression. This paper is prone to benefit lawmakers, regulators, and firm executives responsible for analyzing and assessing enterprise digitization behavior by exploring the influence of macrolevel environmental policy. [ABSTRACT FROM AUTHOR]

Summary: Co‐laminar flow microbial fuel cells (MFCs) with flow‐through electrodes are proposed to improve the power density. Carbon paper was used for the porous electrodes and the membrane‐less MFCs containing a microscale (5.4 μL) anode chamber were microfabricated in a planar monolithic cell for integration with microfluidic devices. The diffusion region between the electrolytes was numerically analyzed and fuel cell performance experiments were conducted with a wastewater inoculum‐based mixed culture biofilm. The effects of the electrolyte flow rate (1‐30 μL min−1) and electrode width (0.5‐2.0 mm) on the fuel cell performance were investigated. The power density was maximized at 692 ± 34 W m−3 under optimal conditions including a 10 μL min−1 flow rate and 1.5 mm electrode width, resulting in suitable biofilm formation and low internal resistance. This study provides valuable information for the commercialization of microfluidic MFCs as a power source for portable medical and electronic instruments. [ABSTRACT FROM AUTHOR]

The rapid deployment of electric vehicles (EVs) in Jordan requires massive efforts to prepare the infrastructures that serve the transportation sector. The lack of EV charging stations is the major obstacle that faces EV drivers. Utilizing renewable energy in EV charging stations contributes to the spread of these stations. Renewable energy technologies are environmentally friendly as they mitigate greenhouse gases that cause the global warming phenomenon. In this paper, an EV charging station, based on a PV-biodiesel-battery hybrid system, is investigated. The importance of this article is to discuss the hybrid system of PV and waste vegetable oil (WVO) along with storage that applies the maximum reliability supply, having an environmentally friendly supply and achieving the lowest energy cost of charging. This station is designed based on renewable and WVO utilization. In fact, WVO, coming from restaurants, is exploited to produce electricity by a diesel generator through direct burning after converting it into biodiesel. The capacity of each station is 14 cars/day with a medium-speed charger of 7 kW. The system is simulated and optimized using iHOGA software where multiobjective optimization is applied to achieve the minimum net present cost (NPC) and CO2 emissions considering three cases, PV-diesel, PV-biodiesel, and PV-WVO, all with battery-hybrid system. These values for the EV charging station that uses the PV-biodiesel-battery hybrid system are 624408 € and 15.4 tons/year, respectively. The corresponding values are 781473 € and 15.14 tons/year and 615310 € and 18.84 tons/year for the systems that work with diesel and WVO, respectively, and energy cost is achieved in best solution to be 0.11 Euro/kWh. Simulation results show that the proposed technique led to enhanced operational efficiency in terms of both NPC and annual CO2 emissions. [ABSTRACT FROM AUTHOR]

In this paper, a new simultaneous framework of distribution network operation is proposed based on the scheduling of photovoltaic/wind/battery multi-microgrids with network reconfiguration considering self-healing. The objective function is considered to minimize the energy losses, and multi-microgrids cost and improve the reliability indices including minimization of energy not-supplied (ENS) and minimizing system average interruption duration (SAIDI) and system average interruption frequency (SAIFI) indices. The optimization variables are defined as the situation of the distribution network switches to find the network's optimal configuration with the installation location and size of renewable resources and battery energy storage during 24 hours. An improved beluga whale optimization (IBWO) based on a nonlinearly diminishing inertia weight (NDIW) approach is used to find the optimal variable set of the problem. The recommended methodology is implemented on 33-bus and real 59-bus distribution networks. The results demonstrated that by obtaining an optimal state of the network switches in the event of a fault, as well as the optimal scheduling of the two microgrids, the energy losses have decreased and the reliability indices have improved. The outcomes of the proposed methodology based on the hybrid multi-microgrid allocation and network reconfiguration are stated that the losses, ENS, SAIDI, and SAIFI are reduced by 66.39%, 54.00%, 50.24%, and 33.61%, respectively, for 33-bus network and are declined by 65.29%, 57.44%, 48.63%, and 62.33%, respectively, for the real 59-bus Ahvaz network in comparison with the base network. The obtained results illustrated that in the condition of the network line outage, by simultaneously implementing the reconfiguration with the change of network switches and the optimal allocation and scheduling of HMGs in the network, self-healing is provided to prevent a significant weakening of the network performance so that the resilience is improved in addition to minimizing the energy losses and the cost of HMG energy injection compared to the base network. The findings revealed that the objectives including losses, ENS, SAIFI, and SAIDI are increased by 78.29%, 33.00%, 83.33%, and 35.11%, respectively, due to outage of line 22 of the 33-bus network and these objectives are increased by 52.32%, 10.30%, 32.29%, and 79.66%, respectively, due to outage of line 12 of the 59-bus network compared with not considering the line outage. Moreover, the superior capability of the recommended NDIW-based IBWO has been confirmed in comparison with the well-known particle swarm optimizer (PSO) and ant lion optimizer (ALO) in solving the problem to achieve better objective value. [ABSTRACT FROM AUTHOR]

The increasing global dependence on fossil fuels for energy has prompted researchers to explore alternative power generation sources that offer higher efficiency, cost-effectiveness, and low environmental impact. Developed countries have been making continuous efforts to reduce their reliance on depleting fossil fuel sources to curb carbon emissions. As a result, hydrogen has gained significant attention among researchers as a potential future fuel that meets all the necessary criteria. Many countries aiming for a hydrogen economy have invested in research on fuel cells. Among various fuel cells, the solid oxide fuel cell (SOFC) has emerged as a commercially viable power source at a small scale. This paper provides an extensive review of the components, materials, design, operation, and integration strategies of SOFCs with existing thermal-based power plants. The performance and prospects of various SOFCs in standalone and hybrid modes are summarized, along with the limitations. Additionally, the research and commercialization efforts that can enhance the potential applications of SOFCs as a sustainable and reliable system in the long term are outlined. [ABSTRACT FROM AUTHOR]

In the past few years, there has been a notable interest in the application of machine learning methods to enhance energy efficiency in the smart building industry. The paper discusses the use of machine learning in smart buildings to improve energy efficiency by analyzing data on energy usage, occupancy patterns, and environmental conditions. The study focuses on implementing and evaluating energy consumption prediction models using algorithms like long short-term memory (LSTM), random forest, and gradient boosting regressor. Real-life case studies on educational buildings are conducted to assess the practical applicability of these models. The data is rigorously analyzed and preprocessed, and performance metrics such as root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) are used to compare the effectiveness of the algorithms. The results highlight the importance of tailoring predictive models to the specific characteristics of each building's energy consumption. [ABSTRACT FROM AUTHOR]

Energy storage systems (ESS) are seeing rapid market growth due to the changing worldwide landscape of electricity distribution and consumption. An ESS must possess the capability to oversee the functioning of the system's modules under abnormal circumstances, while also having the ability to supervise, manage, and optimize the performance of one or more battery modules. At present, the condition of batteries is assessed based on two factors: the level of charge (SOC) and the overall condition (SOH). By using these two characteristics, it becomes feasible to compute the anticipated battery lifespan and evaluate a battery's efficiency. The assessment of SOH is a crucial determinant in guaranteeing the effectiveness, dependability, and security of batteries in electric vehicles (EVs). Nevertheless, the safety issues resulting from the imprecise estimation and forecasting of battery health status have garnered significant attention in academic circles. This study presents a comprehensive evaluation of several SOH monitoring techniques. In order to achieve this objective, various scientific and technical literatures are examined and the corresponding methodologies are categorized into distinct groupings. The groupings are categorized based on the manner in which the procedure is executed: methods and techniques used in experiments and models. This paper provides a comprehensive overview of the benefits and drawbacks of several SOH assessment and prediction techniques, along with the associated obstacles in SOH estimation. [ABSTRACT FROM AUTHOR]

During the development of oil reservoirs, a rapid increase in water cut following reservoir flooding leads to inefficient or ineffective circulation of injected water, rendering a significant portion of the remaining oil in the reservoir inaccessible. The displacement method using polymer particle dispersion systems effectively solves the issue of rapid water breakthrough in oil reservoirs. Owing to the particle phase separation phenomenon, polymer particles can selectively penetrate into the larger pores where water circulation is inefficient, enhance their flow resistance, and thereby achieve equilibrium displacement along with an increased swept volume. This paper investigates the heterogeneous distribution of polymer particles within a porous medium, incorporates the red blood cell dendrite concentration distribution theory from biological fluid mechanics, and develops a mathematical model to delineate the viscosity characteristics of polymer particle dispersion systems, taking into account the phase separation phenomenon. Building on this foundation, it formulates a capillary bundle model for the polymer particle dispersion system specifically designed for oil displacement and proceeds to determine its relative permeability curve. Simulation outcomes reveal that at a water saturation level of 0.063, the concentration of polymer particles in fractured large pore capillaries is markedly elevated, yet capillaries with a pore size under 26 µm remain devoid of polymer particles. With the increase of water saturation, the concentration of polymer particles in large pore capillaries reduces, whereas it progressively augments in medium pore capillaries. Upon reaching a peak water saturation of 0.751, capillaries smaller than 18 µm are entirely free of polymer particles. These findings suggest that the heterogeneous distribution of polymer particles markedly inhibits the percolation capabilities of the dispersed system following a water phase breakthrough, facilitating the entry of more dispersion into oil-laden capillaries and thus enhancing the flow capacity of the oil phase. [ABSTRACT FROM AUTHOR]

In recent times, the significance of renewable energy generation has increased and photovoltaic-thermoelectric (PV-TE) technologies have emerged as a promising solution. However, the incorporation of these technologies still faces difficulties in energy storage and optimization. This review paper addresses these challenges by providing a comprehensive overview of the latest advancements in PV-TE technologies. The paper emphasizes the integration of phase change materials (PCMs) for thermal energy storage, also buttressing the use of encapsulated PCM for thermal storage and efficiency, and the use of hybrid PCM to enhance overall performance. Furthermore, reviews on the use of machine learning techniques for efficient optimization and the integration of thermoelectric modules into tandem perovskite silicon solar cells have been comprehensively analyzed. The advancements in photovoltaic-thermoelectric systems, as reviewed in this article, signify significant progress in attaining sustainable and effective energy production and storage. This review comprehensively addresses the 4Es, underlining their importance. It not only consolidates recent developments but also charts a path for future research in the field of PV-TE technologies, offering precise insights to guide upcoming studies and innovations. [ABSTRACT FROM AUTHOR]

Vibration control has been of great interest to scientists and engineers for many years. Although linear vibration absorbers have been shown to be effective in mitigating vibrations at specific frequencies, their vibration reduction effect is usually limited to a narrow frequency bandwidth. Nonlinear energy sinks have attracted attention due to their better vibration reduction effect over a wider frequency bandwidth. In practical applications, the nonlinear energy sink devices can effectively absorb, dissipate, and convert energy from broadband excitation, so as to achieve vibration reduction and energy harvesting. However, research on energy harvesting based on the nonlinear energy sink is less mature than in linear systems. Multiple parameters of device design (e.g., damping size) affect the actual performance of the nonlinear energy sinks, but there is no exact method to simplify the design of the multiparameter nonlinear energy sinks. Since it is more difficult to implement electromagnetic and electrostatic energy harvesters, more research has focused on piezoelectric energy harvesters. This paper summarizes the research on the nonlinear energy sink and energy harvesting technology, including the introduction of the nonlinear energy sink, energy harvesting based on the nonlinear energy sink, and its application in various fields of energy harvesting. The paper also summarizes some important methods for solving the dynamical equations, as well as their advantages and disadvantages. The conclusions provide an outlook on the subsequent research of the nonlinear energy sink technology, such as the introduction of piezoelectric materials with high energy density, the benefits of balanced vibration suppression and harvesting of vibration energy, and the self-tuning of parameters in complex environments. It provides a powerful reference for the popularization and application of energy harvesting technology based on nonlinear energy sinks. [ABSTRACT FROM AUTHOR]

The conventional overcurrent protection is ineffective in isolating faults in microgrids due to the low fault current levels contributed by inverter-interfaced distributed generations (IIDGs). To extend the microgrid protection methods, the distance protection is considered as a common alternative to detect faults. However, the fault-ride-through (FRT) requirements and the high impedance fault (HIF) detection challenge the application of the conventional distance protection. To solve the two problems, a new inverse-time distance (ITD) protection for medium-voltage AC microgrids was proposed in this paper. The primary ITD protection was designed to meet the FRT requirements, and the backup protection was coordinated to isolate faults. The fault resistance and distributed generation infeed effect on the measured impedance were mitigated by a communication-assisted method proposed in this paper. Owing to the shorter communication channel time in distribution feeders and lower communication investments without a synchronous clock, the proposed method can be used to improve the ITD protection performance. An 11 kV AC microgrid was simulated with different fault types in the islanded mode and grid-connected mode. Time domain simulation verified the effectiveness of the proposed ITD protection. [ABSTRACT FROM AUTHOR]

In pressurized water reactor accident scenarios, the injection of water from the emergency core cooling system (ECCS) (ECC injection) might induce a pressurized thermal shock (PTS), affecting the reactor pressure vessel (RPV) integrity. Therefore, PTS is a vital research issue in reactor safety, and its analysis is essential for evaluating the integrity of RPVs, which determines the reactor life. The PTS analysis comprises a coupled analysis between thermal–hydraulic and structural analyses. The thermal–hydraulic approach is particularly crucial, and reliable computational fluid dynamic (CFD) simulations should play a vital role in the future because predicting the temperature gradient of the RPV wall requires data on the transient temperature distribution of the downcomer (DC). Since one-dimensional codes cannot predict the complex three-dimensional flow features during ECC injection, PTS is one reactor safety issue where CFD simulation can benefit from complement evaluations with thermal–hydraulic system analysis codes. This study reviewed from the viewpoint of the turbulence models most affecting PTS analysis based on papers published since 2010 on single- and two-phase flow CFD simulation for the experiment on PTS performed in the Rossendorf coolant mixing model (ROCOM), transient two-phase flow (TOPFLOW), upper plenum test facility (UPTF), and large-scale test facility (LSTF). The results revealed that in single-phase flow CFD simulation, where knowledge and experience are sufficient, various turbulence models have been considered, and many analyses using large eddy simulation (LES) have been reported. For two-phase flow analysis of air–water conditions, interface capturing/tracking methods were used in addition to two-fluid models. The standard k – ε and shear stress transport (SST) k – ω models were still in the validated phase, and various turbulence models have yet to be fully validated. In the two-phase flow analysis of steam–water conditions, many studies have used two-fluid models and Reynolds-averaged Navier-Stoke (RANS), and NEPTUNE_CFD, in particular, has been reported to show excellent prediction performance based on years of accumulated validation. [ABSTRACT FROM AUTHOR]

Machine learning (ML) algorithms are increasingly used in power systems applications. One important application is the classification and localization of various types of transmission line faults. Using voltage and current measurements from phasor measurement units (PMUs), a number of useful features can be extracted, which can form the basis of a ML-based prediction of the fault type, line, and distance on the line. This paper proposes a technique to find the optimal number and placement of PMUs by performing thorough feature selection. The features are selected to maximize the accuracy of the ML classification and regression algorithms. The results show that for the IEEE 14 bus system, the use of only five PMUs is sufficient to obtain high levels of accuracy. For example, a testing accuracy of 99.0% and 97.1% can be achieved for the fault type and fault line location, respectively. As for the fault distance along the line, the testing MAE of 3.1% can be obtained along with an R 2 score of 94.4%. Adding more PMUs does not provide any additional value in terms of accuracy. [ABSTRACT FROM AUTHOR]

Recent experience with the strongest earthquakes greater than magnitude 5.4 in Korea leads to public interest in the safety and resilience of critical infrastructures. There are many nuclear power plants near the epicenters of the earthquakes. Nuclear power plants are essential infrastructures that provide stable and enough energy for human life, and simultaneously, control systems for the safety and security of nuclear power plants are critical due to the risk of nuclear accidents on public health and the environment. The nuclear area uses probabilistic risk assessment to estimate the risk of structures, systems, and components in nuclear power plants, and the evaluation of the fragility curve is a key process for probabilistic risk assessment. The challenges of a seismic fragility analysis lie in estimating the influence of various uncertainties in material, geometry, and earthquake and improving the existing fragility analysis methods, which require time-consuming nonlinear time history analysis. Thus, this paper conducts a multivariate seismic fragility analysis using surrogate models for reinforced concrete squat shear walls and proposes a simplified closed form equation for a chosen surrogate seismic demand model. The surrogate models are trained and validated by several approaches: response surface method, support vector machine, Gaussian process regression, and neural network. In addition, a correlation analysis is used to evaluate the relative importance of the variables to the seismic demand to simplify the surrogate model further. Finally, simplified surrogate models based on the importance of the variables are proposed as closed form of polynomials, and the performance of these models on the fragility analysis is evaluated. [ABSTRACT FROM AUTHOR]

Shell and tube-type crossflow heat exchangers with circular fins are widely used in various industries, including nuclear power plants. This study focuses on the sodium-to-air heat exchanger, which is one of the key safety features in sodium-cooled fast reactors. Tube alignment inside the heat exchanger is important because it directly determines the performance. Although heat exchangers are generally designed to have staggered tube alignment, inevitable inline-aligned zones exist. Therefore, this paper proposes a hybrid tube alignment modeling approach that considers both staggered and inline tube heat transfer phenomena. The results of the hybrid model calculations are verified and validated with liquid sodium experiments. The hybrid approach to the tube arrangement reduced the temperature deviation between experimental and calculated values to a difference of 4.55% and 7.38% for both sodium and air sides, respectively, while for the heat transfer, the difference was 15.12% and 9.06% for sodium and air sides, respectively. The results of this study can also be used as a basis for the safety evaluation of nuclear reactors and licensing processes for sodium-cooled fast reactors. In addition, this study is limited not only to sodium heat exchangers but also to any serpentine tube arrangement or crossflow heat exchanger under high-temperature systems, such as concentrated solar power and thermal energy storage industries. [ABSTRACT FROM AUTHOR]

This paper performs a technoeconomic analysis of the wind power potential and evaluates the cost of wind power generation in Evodoula, comparing two methods, the conventional method and the uncertainty method based on a comparative spatiotemporal approach using the geographic information system (GIS) software tool. This study is based on satellite wind data measured at 10 m above ground level (AGL) over a 40-year period (1980-2019), by the meteorological service NASA (National Aeronautics and Space Administration)/Goddard Space Flight Center (GSFC). The main objectives are to obtain an appropriate design for a proven optimal location and to assess the viability of wind power at Evodoula. For this type of study, there is little literature available. The optimization of an onshore wind farm and deployment in the wind energy development interest area (ZIDEE) is carried out to obtain a minimum and parsimonious discounted cost production unitary (CPU) of the electricity produced. The results showed that in Okok, a location with a large energy deficit, an onshore wind farm with an electricity generation capacity of 12.5 MW with 5 NORDEX N100-2.5MW wind turbines would have a total energy production (TEP) of about 64.0254825 TWh and a selling price of electricity that would be 0.0034 CAD$/kWh, which is very low compared to the utility price (about 98% cheaper). The total cost of the wind farm would be about $11 million, with a net present cost of about $218 million. The annual profit generated by the wind farm would be over $6 billion. The return on investment (ROI) of the project is estimated at 2880.882%. The constructed onshore wind farm would avoid CO2 emission at over 11 Mt CO 2 , eq /year as the energy generated is from the atmosphere. The wind farm would realize an average annual cash flow estimated at nearly $30 million after 20 years of operation. These savings would allow the installation of CO2 capture systems in conventional power plants. In addition, the analysis of uncertainties and risks was identified and quantified to estimate the confidence levels of the project development results. The risks have been assessed, and we recommend that the total uncertainty of the project is around 15%. The energy values in P 75 and P 90 are 10.08% and 19.22%, respectively, lower than the energy value in P 50 of 11.60 GWh/An. Finally, the main policy recommendations for an inclusive design process are highlighted. The contribution of this study is to assist policy makers in making appropriate decisions in the development and implementation of energy and environmental policy in Cameroon and in many continental areas. [ABSTRACT FROM AUTHOR]

The reliability of a pressurized water reactor power plant's control rod drive mechanism (CRDM) is affected by many factors, such as operation states, unit performance, and dynamic environments. Multiple sources of uncertainties, including random, interval, and fuzzy, exist when analyzing the reliability of CRDMs. Modeling reliability without considering the fusion of multisource uncertainties may result in model distortion and may not provide realistic assessment results. This paper proposes a multisource uncertainty fusion method powered by the margin-based variable transformation and the Bayesian network propagation. The interval and fuzzy variables are transformed into random variables to obtain the corresponding generalized probability density function of the CRDM's feature parameters. After that, the CRDM's reliability can be evaluated via probability quantization of the Bayesian network inference result through sampling algorithms. A magnetic-jack type CRDM case is presented to verify the proposed method, and the results show that this method can fuse three types of uncertainty variable in a unified way and effectively obtain reliability evaluation results. [ABSTRACT FROM AUTHOR]

The need for sustainable integrated energy systems to mitigate environmental impact is hindered by challenges in fluctuating demand, trading reliability, and trustworthiness. This paper proposes an innovative approach to tackle these challenges by introducing a blockchain-based integrated energy system trading model with smart contracts. It is intricately linked with the operation of carbon capture and storage (CCS) technology and power-to-gas (P2G) equipment. The CCS-P2G-coupled operation principle is first outlined, followed by the presentation of a comprehensive system model. The peer-to-peer (P2P) energy trading algorithm is enhanced using the Bloom filtering technique. Leveraging smart contracts, a distributed energy trading mechanism is employed, resulting in a meticulously constructed integrated energy system trading model for CCS-P2G-coupled operation. The proposed model is rigorously evaluated for energy trading efficiency and system performance, revealing significant improvements compared to prior studies and showcasing substantial cumulative benefits. Three operation scenarios are examined, with experimental results highlighting the model's superior carbon emission reduction capacity. This study introduces an innovative paradigm for trading and managing integrated energy systems, holding potential implications for the sustainable development and decarbonization transition of future energy systems. [ABSTRACT FROM AUTHOR]

In the past few years, different kinds of structural nonlinearities, such as external magnetic interaction and multistable structures, have been introduced into galloping energy harvesters to enhance energy harvesting efficiency. However, since the galloping-based piezoelectric energy harvester (GPEH) is a self-excited system, the conventional impedance matching method that is widely used in vibration energy harvesters is no longer valid for it. Therefore, the power characteristics of the nonlinear GPEH are still an open question to be solved. To this end, this paper is motivated to derive the approximate analytical solution of a monostable galloping-based piezoelectric energy harvester through the harmonic balance method and impedance matching theory. The analytical maximum power, power limit, and critical electromechanical coupling are studied from the perspective of the influence of structural nonlinearity on the power performance. Firstly, the approximate analytical solutions of output power, power limit, optimal resistance, and critical electromechanical coupling coefficient are derived. The accuracy of the analytical solution is verified by numerical simulation. It is found that the influence of structural nonlinearity on the power characteristics of the nonlinear GPEH is quite different under different wind speeds. After that, the power characteristics of the system under different wind speeds and different coupling conditions are investigated. The results showed that the maximum power of the system can be increased by introducing stiffness nonlinearity under low wind speed and weakly coupled configuration. Even more, the system can be shifted into a strongly coupled system when the nonlinearity is enhanced to a certain level. Reasonable design of stiffness nonlinearity can effectively reduce the critical electromechanical coupling, which indicates that stiffness nonlinearity is a feasible and effective way to improve the power performance of low-speed wind energy harvesting. [ABSTRACT FROM AUTHOR]

This paper investigates comprehensively the operational dynamics of a thermochemical heat storage (TCHS) reactor for low-temperature applications using polyaluminum sulfate and takes into consideration a developed simulation model with an experimentation validation. Significant concordances were found between the developed simulation model and the experimental results. Results reveal optimized conditions for the charging process using an electrical heater, with a heating temperature of 120°C at 10 K/min over 500 minutes. This achieves full material charging, with stabilized pressure drops at an equilibrium of 80 mbar, corresponding to a temperature of approximately 108°C, and yielding a thermal power of 950 W. An inlet vapor pressure of 18 mbar at 10°C for 5 hours is sufficient to completely discharge the bed, with pressure drops reaching around 30 mbar and a thermal power of 300 after reaction completion. Insights into conversion extents during both processes are provided, along with a remarkable thermal efficiency of 90% and a coefficient of performance (COP) of 97%, surpassing recommended theoretical values (50%). The study suggests further enhancing system performance through the design and implementation of a dedicated heat exchanger. The achievement of 75% of the targeted thermal power specification represents a significant milestone, offering valuable contributions towards the realization of sustainable technological advancements of both the reactor technology of TCHS and state-of-the-art thermal energy storage solutions. From the research, it is possible to infer further suggestions for enhancing this performance by designing and implementing a dedicated heat exchanger for both heat supply and retrieval mechanisms. [ABSTRACT FROM AUTHOR]

Due to its cost-effectiveness and high product selectivity, tin oxide has been regarded as a promising catalyst for the electrochemical conversion of CO2 to formate. However, formate production is hindered by the high overpotential; there is a need to reduce the overpotential to enhance energy efficiency and lower electricity cost for the implementation of carbon utilization technology. Here, we report a facile synthesis method for 1 nm-sized SnO2 cluster catalysts, which can be used for CO2-to-formate conversion. SnO2 clusters were prepared through impregnation of porous carbon with a tin precursor solution. The SnO2 clusters showed a low overpotential, generating a current density of 10 mA cm-2 at a potential of -0.34 V vs. RHE in 1 M KOH. They also achieved high Faradaic efficiencies of 90.5% and 81.5% at 200 and 300 mA cm−2, respectively. Their electrocatalytic performance was strongly dependent on the annealing conditions, which affected the particle size, electrochemical active surface area, and metal oxidation state. This paper presents a versatile method for synthesizing metal oxide cluster catalysts, apart from providing insights into the catalytic activity for the electrochemical conversion of CO2 to formate. [ABSTRACT FROM AUTHOR]

Photovoltaic power generation can directly convert solar energy into electricity, but most of the solar energy absorbed by the photovoltaic panel is converted into heat, which significantly increases the operating temperature leading to a reduction in the power generation efficiency of the panels. To reduce the working temperature of photovoltaic panels and improve the photoelectric conversion efficiency, this paper installs aluminum fins and air channels at the traditional photovoltaic cell back sheets and cools them with forced-circulation cooling through fans. The relationships between fin spacing, fin height, air channel inlet wind speed and panel temperature, power generation, and electrical efficiency were investigated. The results show that the temperature of the photovoltaic panel decreases and then increases with the decrease of the fin spacing during natural convection and gradually decreases with the increase of the fin height. The use of forced-circulation cooling technology can effectively reduce the PV panel temperature and increase the net power generation. When the solar radiation intensity is 1000 W/m2, the ambient temperature is 35°C, the fin spacing is 6 mm, the height is 80 mm, the inlet wind speed is 1 m/s, the net generating power reaches the maximum value, and the net generating power and the electrical efficiency are increased by 14.6% and 2.25%, respectively. [ABSTRACT FROM AUTHOR]

This paper proposed a single-piston free piston expander-linear generator (SFPE-LG) prototype applied to organic Rankine cycle systems. Two valve timing control strategies, namely, time control strategy (TCS) and position control strategy (PCS), were developed. Based on the experimental data, a back propagation neural network (BPNN) prediction model was established. The effects of structural parameters such as neural network layers, transfer function, training function, hidden layer nodes, and learning rate on the prediction accuracy of this BPNN model were discussed. The training and prediction accuracy of the BPNN model was verified using 5-fold cross-validation and Wilcoxon signed-rank test. Moreover, the BPNN model was integrated with a genetic algorithm to predict and optimize the maximum output power of the SFPE-LG. The results showed that the BPNN model used to predict the motion characteristics and output performance of the SFPE-LG exhibits strong learning ability and high prediction accuracy. Notably, the prediction accuracy of the BPNN model is significantly higher under the PCS compared to TCS. The effect of hidden layer nodes on mean square error (MSE) and correlation coefficient (R) is greater than that of the learning rate. When the number of hidden layer nodes exceeds 30, the BPNN model consistently achieves low MSE and high R. The optimization results showed that the SFPE-LG can obtain a maximum output power of 141.69 W under the TCS, when the working parameters are inlet pressure of 0.7 MPa, intake duration of 35 ms, load resistance of 67 Ω, and expansion duration of 104 ms, respectively. [ABSTRACT FROM AUTHOR]

While demand response programs inherently depend on consumer acceptance in order to be successful, consumer behavior is often overlooked when designing such programs. This paper addresses the impact of consumer flexibility in terms of appliance use on the success of a demand response program, measured through the overall grid stability assessed by the demand's peak-to-average ratio. We employ a bootstrapping approach to simulate energy communities from real-life consumer data and implement a state-of-the-art demand response system. Results suggest that higher consumer flexibility under real-time energy tariffs implies higher degrees of grid stability, with real-time pricing decreasing the average peak-to-average ratio by 4.6% compared to time-of-use tariff and with highly flexible consumers showing a 23% lower peak-to-average ratio than regular consumers on average. Yet, it is possible for higher flexibility to be detrimental to grid stability by increasing the peak-to-average ratio under a time-of-use tariff. This result highlights the importance of understanding the interplay between different factors that influence energy consumer behavior, a research stream that has been under investigated thus far. [ABSTRACT FROM AUTHOR]

This paper presents a multistrategy fusion particle swarm optimization model for dynamic economic dispatching of renewable energy in distribution networks. The objective is to minimize active network losses and system voltage deviation while considering the integration of distributed energy sources and static reactive power compensators. The algorithm incorporates specific strategies, including a particle position change strategy based on the midpipeline convergence approach, a strategy for generating exploding particles near the optimal particles, and a particle velocity update strategy relying on the global optimal particle position. The inertia weights and particle position update methods of the simplified particle swarm optimization algorithm are also utilized. Simulation experiments are conducted on an IEEE 33 bus radial distribution system, demonstrating the effective optimization of system losses while ensuring system voltage stability. This research contributes to the scientific understanding of renewable energy integration in distribution networks and its economic dispatching. [ABSTRACT FROM AUTHOR]

Stochastic programming has become increasingly vital in energy applications, especially in the context of the growing need for renewable energy solutions. This paper presents a significant advancement in this field by introducing an efficient and robust algorithm for optimally sizing hybrid renewable energy systems. Utilizing a two-stage stochastic programming approach, the proposed algorithm addresses the challenges posed by the unpredictability of renewable energy sources. The proposed solution leverages the three-block alternating direction method of multipliers (ADMM), a cutting-edge technique that facilitates parallel computation and enhances computational efficiency. The distinctiveness of this method lies in its ability to solve complex stochastic optimization problems without compromising the mathematical integrity of the model. This is achieved by applying first-order optimality conditions, ensuring both robustness and efficacy. To demonstrate the practical applicability and superiority of the algorithm, a case study was conducted in a rural area of South Africa. The proposed algorithm was applied to design an optimal hybrid renewable energy system, and its performance was compared against traditional methods such as progressive hedging and Monte Carlo techniques. Results affirm the superiority of the approach, saving approximately 8.16% capital cost when compared to progressive hedging. In addition, the proposed algorithm outperforms the Monte Carlo method both in terms of CPU time and the number of cost function evaluations. [ABSTRACT FROM AUTHOR]