Transmission Energy Research Articles

The role of structural and insulating material in the structure-borne noise propagation of superyachts

The insulation and noise and vibration damping characteristics of complex systems used by humans, such as automobiles, airplanes and ships are becoming increasingly important from the early design stages to ensure an adequate level of comfort. Especially in the naval fields, the design of insulation plans is crucial to prevent the propagation of noise and vibrations on board of megayachts. Since it is quite complex to identify and correctly model the sources due to their deterministic and random nature, during the early design stage, the focus is on insulation rather than reducing the acoustic levels of the sources themselves. In this article, a method for analyzing sea trials on a superyacht will be proposed with the aim of analyzing how much the insulation materials can limit the levels of vibrational energy on board during the path between sources and receivers. A new a descriptor based on harmonic transmission energy through the structure is proposed for path insertion loss experimental identification. In particular, by using spectral analyses and synchronous averaging of sound levels in various areas of the superyacht, it will be possible to study the vibroacoustic insulation of structural materials and their damping coefficient.

Long-wave infrared multi-spectral filter arrays based on surface plasma polaritons

An infrared multi-spectral filter based on surface plasmon polaritons is proposed in this study. It is used to achieve optical filtering in the long-wave infrared range of 8-14μm. After coupling with the plasma polaritons excited on the surface of Au film, the incident light propagates through periodic sub-wavelength through-holes. We analyzed the transmission characteristics of the filter with periodic sub-wavelength through-holes and its local field distribution using the Finite-Difference Time-Domain (FDTD), and carried out the tolerance analysis to demonstrate the possibility of large-scale and low-cost processing. The simulation results indicated that our proposed filter attained four spectral channels in the spectral range of 8 to 14 μm with peak energy transmittance up to about 60%, and wide tolerances as well as polarization-insensitive characteristics. Our proposed long-wave infrared filters can provide efficient and low-cost solutions for lightweight multi-spectral devices and all-weather detection.

Significant dependence of the efficiency of energy-saving thermochromic VO2 on slight changes of its properties in the visible due to strain and/or vacancies

There are worldwide efforts to maximize the energy saving achieved by VO2-based thermochromic coatings. In particular, there are very different values of the modulation of integral solar energy transmittance, reported by various laboratories on various templates even for seemingly very similar coatings. A detailed analysis reveals that this is largely due to the combination of the intentional and well understood transmittance modulation in the infrared (always beneficial) with not yet understood slight transmittance modulation in the visible (sometimes beneficial, sometimes harmful, and always multiplied by strong solar irradiance). Ab-initio calculations are used to examine the hypothesis that the transmittance modulation in the visible can be controlled by lattice strain and/or slightly off-stoichiometric [O]/[V] ratio. The presented phenomenon opens a pathway which may lead, in a case of reproducible preparation of correctly altered VO2, to significantly enhanced energy saving.

Investigating the Effect of the Yellow Chlorophyll on the Characteristics of Liquid Polyethylene Glycol for Liquid Electrolyte Solar Cells

In this study, polyethylene glycol (PEG) and natural dye were employed to make the liquid electrolyte media for solar cells. To prepare varied amounts of dye, the yellow dye of the flowers was extracted using diluted ethanol via ionized water. To produce a constant concentration of all polymer liquids, 10g of PEG dissolves in 1000 ml of solvents including: (di-water, dilute dye, and concentrated dye) individually. The viscosity of solutions was determined using an Ostwald viscometer at various temperatures. Optical parameters such as transmittance, absorbance, and indirect energy gap were investigated utilizing the ultraviolet spectrum. The results reveal that increasing the temperature causes the viscosity decreases and the solar cell efficiency increases. When the dye concentration is increased, the absorbance and absorption coefficient increase, while the transmittance decreases. After adding the concentrated dye, the energy gap of liquid PEG reduces from 1.4 eV to 0.6 eV. PEG with concentrated dye, on the other hand, is the best sample based on the energy gap value. As a result, four concentrations of PEG liquid were prepared: (0.02, 0.025, and 0.03) w/v concentrations, followed by the addition of the concentration dye in the same quantity for each concentration of PEG liquid. Four prepared liquids were tested for viscosity. The results showed that the viscosity of PEG + concentrated dye decreased as the PEG concentration was increased. When the concentration of PEG solution without dye is increased, the viscosity of PEG liquids increases.

Improvement of the Low-Energy Adaptive Clustering Hierarchy Protocol in Wireless Sensor Networks Using Mean Field Games

The Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol is a widely used method for managing energy consumption in Wireless Sensor Networks (WSNs). However, it has limitations that affect network longevity and performance. This paper presents an improved version of the LEACH protocol, termed MFG-LEACH, which incorporates the Mean Field Game (MFG) theory to optimize energy efficiency and network lifetime. The proposed MFG-LEACH protocol addresses the imbalances in energy consumption by modeling the interactions among nodes as a game, where each node optimizes its transmission energy based on the collective state of the network. We conducted extensive simulations to compare MFG-LEACH with Enhanced Zonal Stable Election Protocol (EZ-SEP), Energy-Aware Multi-Hop Routing (EAMR), and Balanced Residual Energy routing (BRE) protocols. The results demonstrate that MFG-LEACH significantly reduces energy consumption and increases the number of packets received across different node densities, thereby validating the effectiveness of our approach.

On the value of Fano resonance in wave energy converters

The article evaluates the potential of the Fano resonance operational principle in wave energy converters (WECs), using a 2-body loosely moored self-referenced WEC as an illustrative example. By leveraging Fano resonance, the point absorber buoy can remain relatively stationary with low loading on mooring lines, serving as an efficient wave energy transmitter while concurrently achieving resonance within the internal power take-off (PTO) system. This arrangement reduces the motion of the point absorber hull, thereby decreasing loads on the WEC structure, mooring lines, and anchors. As a result, operational and structural costs are minimised, further reducing the levelised costs of generated energy. Additionally, by ensuring minimal fluctuations in the WEC, confidence in using traditional linear mathematical models is increased, as commonly employed for WEC performance assessment and control design.The article presents a resonance study and introduces newly derived solutions in the frequency domain for the proposed operational concept. It analytically demonstrates the viability of employing the Fano resonance operational strategy for WECs, suggesting that this strategy has the potential to compete with traditional methods of wave energy transformation. Furthermore, the insights gained from the study contribute to identifying optimal parameters for a PTO system, as well as optimising the design of the heaving buoy.

Straightforward Synthesis Methodology for Obtaining Excellent ORR Electrocatalysts From Biomass Residues Through a One Pot‐High Temperature Treatment Approach

AbstractMaterials prepared from biomass residues are potential candidates to substitute the Pt‐based commercial electrocatalysts in oxygen reduction reaction (ORR). Although some investigations have reported activity and durability comparable to Pt/C using biomass‐derived catalysts based on Fe─N─C sites, it remains a challenge to decrease the environmental impact of the production of these materials. A straightforward procedure is developed to obtain excellentORR electrocatalysts from biomass residues which requires a single high‐temperature treatment. The final washing step is avoided by optimizing the initial amount of Fe precursor (FeC2O4). Besides the formation of iron oxide nanoparticles, a highly dispersed Fe phase is detected by High Angle Annular Dark Field Scanning Transmission Electron Microscopy and Energy Dispersive X‐Ray Spectroscopy (HAADF‐STEM‐XEDS) analysis as well as graphitic carbon structures. The best performance for almond shell‐based electrocatalysts is achieved for the sample containing 4.6 wt. % of Fe. The procedure developed is also applied to oceanic posidonia and eucalyptus residues, also showing excellent ORR behavior. The best sample is studied in a primary Zn‐air battery (ZAB) obtaining a maximum power density of 59 mW cm−2 and 755 mAh gZn−1 capacity.

Enhancing anti-adhesion properties by designing microstructure - the microscopy and spectroscopy study of the intercellular bacterial response.

This study is the first one that investigates in detail the bacterial intercellular response to the high density of crystallographic defects including vacancies created in Cu by high pressure torsion. To this aim, samples were deformed by high pressure torsion and afterward, their antibacterial properties against Staphylococcus aureus were analyzed in adhesion tests. As a reference an annealed sample was applied. To avoid the influence of surface roughness, specially elaborated conditions for surface preparation were employed, which do not introduce defects and assure comparable surface roughness. The analysis of the chemical composition and thickness of passive layers by X-ray photoelectron spectroscopy showed that they were comparable for nanostructured and micrograined samples, consisting of Cu2O and CuO, and a thickness of 6nm. The interface bacterium-substrate was prepared by a focused ion beam and further analyzed by scanning transmission electron microscopy and energy dispersive spectroscopy. High pressure torsion processed Cu shows enhanced anti-adhesion properties while in contact with S. aureus than micrograined Cu. There is a linear correlation between luminous intensity and grain size-0.5. The bacterial intercellular defence mechanism includes the creation of Cu2O nanoparticles and the increased concentration of sulphur-rich compounds near these nanoparticles.

Design and Scalable Synthesis of Thermochromic VO2-Based Coatings for Energy-Saving Smart Windows with Exceptional Optical Performance.

We report strongly thermochromic YSZ/V0.855W0.018Sr0.127O2/SiO2 coatings, where YSZ is Y-stabilized ZrO2, prepared by using a scalable deposition technique on standard glass at a low substrate temperature of 320 °C and without any substrate bias voltage. The coatings exhibit a transition temperature of 22 °C with an integral luminous transmittance of 63.7% (low-temperature state) and 60.7% (high-temperature state) and a modulation of the solar energy transmittance of 11.2%. Such a combination of properties, together with the low deposition temperature, fulfills the requirements for large-scale implementation on building glass and has not been reported yet. Reactive high-power impulse magnetron sputtering with a pulsed O2 flow feedback control allows us to prepare crystalline W and Sr codoped VO2 of the correct stoichiometry. The W doping of VO2 decreases the transition temperature, while the Sr doping of VO2 increases the luminous transmittance significantly. A coating design utilizing second-order interference in two antireflection layers is used to maximize both the integral luminous transmittance and the modulation of the solar energy transmittance. A compact crystalline structure of the bottom YSZ antireflection layer further improves the VO2 crystallinity, while the top SiO2 antireflection layer provides also the mechanical and environmental protection for the V0.855W0.018Sr0.127O2 layer.

Medium- and Long-Term Distributed Photovoltaic Power Prediction Based on Multiple Time Series Feature and Multiple-Model Fusion

Distributed photovoltaic power stations have advantages such as local direct power supply and reduced transmission energy consumption, and whose demands are constantly being developed. Conducting research on medium- and long-term distributed photovoltaic prediction will have significant value for applications such as the electricity trade market, power grid operation, and the planning of new power stations. Due to characteristics such as long time dependence, disperse power stations, and strong randomness, making accurate and stable predictions becomes very difficult. In this research, we propose a multiple time series feature and multiple-model fusion-based ensemble learning model for medium- and long-term distributed photovoltaic power prediction (M2E-DPV). Considering the wave influence and the differences in distributions in different areas of photovoltaic power, multiple feature combinations are designed to increase feature expression ability and adaptability. Based on the boost ensemble learning model, trained on a single model of different time scale features, the optimal scoring strategy is used for multiple model fusion in the rolling prediction process, and finally, time-segmented probabilistic correction is performed. The experiment results show the effectiveness of the M2E-DPV under multiple feature combinations and multi-model fusion strategies. The average MAPE, R2, and ACC indicators are 0.15, 0.96, and 0.91, respectively. Compared with other methods, there is a significant improvement, indicating that the prediction ability of the model framework proposed in this paper is advanced and robust.

Energy-saving clustering routing algorithm for heterogeneous wireless sensor networks based on energy iteration model and bee colony optimization

Aiming at the problems of large number of data transmission node deaths and large transmission energy consumption output in energy-saving clustering routing communication of wireless sensor networks, an energy-saving clustering routing algorithm for heterogeneous wireless sensor networks based on energy iteration model and bee colony optimization is proposed. Firstly, a network communication energy consumption model is constructed, and the network node distribution is optimized in time with the goal of reducing energy consumption combined with differential bee colony algorithm; then, based on the network node distribution optimization results, an energy-saving clustering method for heterogeneous wireless sensor networks is formulated, and the cluster head is determined by using the energy iteration cluster selection method, and the cluster head radius is obtained to complete the energy-saving clustering of communication nodes in heterogeneous wireless sensor networks; finally, the distance between the communication cluster head node and the base station is set, the routing level of the node communication is determined, and the energy-saving routing communication of the heterogeneous wireless sensor network is realized by combining the multi-hop routing communication mode. The experimental results show that when the method is used for network energy-saving clustering routing communication, the number of data transmission nodes that die is at most 22, and the maximum energy consumption of node transmission is 21 nJ/bit , indicating that the node communication energy-saving effect of this method is good.

Dual-wavelength transmission based on liquid crystal tunable filter with high signal-to-noise ratio

Aiming at the problem of limited transmission energy of liquid crystal tunable filter (LCTF), a dual-wavelength transmission system with high signal-to-noise ratio (SNR) is proposed in this paper. The proposed transmission factor Qp is the main influence on the number and location of transmission wavelengths as well as the bandwidth of each transmission wavelength for dual-wavelength systems. Dual-wavelength LCTF can improve the effective transmission energy of the system by increasing the number of filtering channels, and the transmission energy can be increased by about 1.8 times and 70% at short and long wavelengths, respectively, which improves the signal-to-noise ratio (SNR) of the system. Moreover, the dual-wavelength LCTF system is even possible to increase the transmission energy by about 7% at a 33% increase in spectral resolution. Therefore, the dual-wavelength LCTF transmission method not only can improve the SNR of target detection with dual-wavelength response features, but also can effectively solve the problem of contradiction between spectral resolution and spectral transmission energy.

A brief analysis of spectral technology for effective utilization of full spectrum of solar energy

In this paper, a spectroscopic technology based on a trough-type parabolic condenser is proposed, which effectively utilizes the full spectrum of solar energy for light transmission through optical fibers. The technology comprises four parts, which are concentration, transmission, splitting, and detection, and its application in the field of clean energy was explored. A one-way glass is introduced into the installation as a device for light transmission restriction. The one-way transmittance of one-way glass effectively ensures the transmission direction of sunlight. According to the light simulation results from TracePro software, after the light was transmitted through the one-way glass reflection device, light intensity was guaranteed to meet usage requirements. After being focused by collimating lens and Fresnel lens, the light is introduced into a Roland circle spectroscopic system through an optical fiber. After splitting, various types of light passing through the detection system are introduced into their respective optical fibers for long-distance transmission and use. From the experiments, it was found that through reasonable splitting and the targeted use of different wavelength bands, the effective utilization of the full spectrum of solar energy significantly improved, verifying the feasibility of the device design idea.

Effect of temperature on seasonal wind power and energy potential estimates in Nordic climates

AbstractA major obstacle standing in the way of full‐scale adoption of renewable energy sources is their intermittency and seasonal variability. To better understand the power generation dynamics, the effect of air density due to temperature on power and energy generation figures was modelled. The model uses historical ERA5 data and considers changes in weather patterns in a subarctic climate where seasonal changes are most pronounced. The power generation figures of using a mean and a dynamic air density value were compared and the results show that power generation estimates may be under‐ and overestimated by on average 5% up to 10% in winter and summer, respectively. This can have implications for the sizing of power transmission infrastructure and energy storage in both on‐grid and off‐grid applications as well as power availability. The topic is highly relevant in the Nordic countries where roughly 10% of new global added wind capacity is installed annually.

Ag modified ZnO nanoflower gas sensitive sensor for selective detection of n-butanol

Ag modified ZnO nanoflowers were successfully prepared by sunlight induced solvent reduction method. The samples were characterized by x-ray diffractometer, field emission scanning electron microscope, transmission electron microscope and energy dispersive x-ray spectrum, and the results confirmed the presence of Ag nanoparticles on the ZnO nanoflower. The gas sensing performance of the materials was studied at different operating temperatures and different n-butanol concentrations. The results showed that the Ag modified ZnO nanoflower sensor responded to 50 ppm n-butanol up to 147.17 at 280 °C, and the Ag modified ZnO nanoflower sensor exhibited excellent repeatability, stability and response recovery time. In addition, different target gases were employed for the selectivity study of the Ag modified ZnO nanoflower. It can be found that the Ag modified ZnO nanoflower had good selectivity for n-butanol. The improved response of the Ag modified ZnO nanoflower sensor was attributed to the catalytic effect of Ag nanoparticles. The results indicate that the Ag modified ZnO nanoflower will become a very promising sensing material for n-butanol gas detection.

Cu-Atom Locations in Rocksalt SnTe Thermoelectric Alloy.

The development of functional thermoelectric materials requires direct evidence of dopants' locations to rationally design the electronic and phononic structure of the host matrix. In this study, Cs-corrected scanning transmission electron microscopy and energy dispersive X-ray spectroscopy is employed at the atomic scale to identify Cu atoms' locations in a Cu-doped SnTe thermoelectric alloy. It is revealed that Cu atoms in the rocksalt SnTe form solid solutions at both Sn and Te sites, contrary to their electronegativity order and the intentional Cu doping at Sn sites. Cu atoms are also located at the tetrahedral and crowdion sites of the face-centred cubic structure, with varying degrees of correlations. Such high flexibility of Cu atoms in the rocksalt SnTe offers diverse phonon-scattering mechanisms conducive to the ultra-low lattice thermal conductivity of singly Cu-doped SnTe. This study offers atomic-scale insights for achieving more precise dopant engineering, leading to the accelerated development of functional thermoelectric materials.

Efficient multichannel energy harvesting with dedicated energy transmitters in CR-IoT networks

Radio Frequency (RF) energy harvesting is strongly believed to be a sustainable solution to the power depletion problem in battery powered IoT devices. In addition to harvesting energy from ambient RF signals, the use of dedicated energy transmitters (ETs) that transmit energy to nearby IoT devices via RF signals has recently been proposed. In this paper, we study the problem of designing an energy harvesting policy for a group of cognitive radio-enabled IoT (CR-IoT) devices served by a number of ETs to maximize the minimum of their charging rates. With the help of cognitive radios, a CR-IoT node is capable of changing its frequency channel of operation allowing for multi-channel energy harvesting. Frequency channels are assumed to be opportunistically accessible depending on the activity of wireless users that are licensed to use those channels. The problem entails the design of the ET’s transmission policy (to what CR-IoT device, and over what channel) and the design of an ambient harvesting policy for every CR-IoT device (when it is not served by ETs). The problem is formulated as a mixed integer linear program (MILP). The objective is to maximize a lower bound on the total harvested energy in a given time frame per CR-IoT node. This optimization is subject to scheduling, total energy budget, and maximum transmit power constraints. Given the intractability of MILP formulations, a sub-optimal algorithm is proposed. Extensive experimentation is carried out to assess the effectiveness of the proposed sub-optimal algorithm by comparing it to the MILP’s solution obtained using IBM CPLEX solver with a limit on the execution time. We also combine our sub-optimal algorithm withe the CPLEX solver to produce a new two-stages algorithm that improves the original one by around 47%. Finally, we investigate the effect of multiple parameters including number of ETs, number of channels, and channel availability probability on the minimum charging rate.

Communication Technology for Renewable Energy Access Grid System Based on Multi-source Heterogeneous Data Fusion

Abstract Incorporating renewable energy solutions into the power grid is essential for facilitating a shift in energy sources. Ensuring the effectiveness and dependability of communication technologies within smart distribution grids is vital, as these grids serve as the link between end users and the central station, thereby contributing to the grid’s stable functioning and the effective dissemination of energy. This study introduces a framework for communication that tackles the challenges associated with the integration of multi-source, heterogeneous data in smart distribution grids. The framework leverages multi-source heterogeneous data fusion and capitalizes on edge computing to efficiently process and consolidate data from diverse sensors and devices. An optimal weight allocation algorithm is proposed to mitigate data redundancy and to improve the energy efficiency of communication. The paper demonstrates, through theoretical examination and empirical tests, the proposed system’s enhanced communication capabilities, especially in terms of data transmission effectiveness and energy usage optimization. The discussion highlights the advantages of smart distribution networks over conventional communication methods and offers insights for further advancements in communication technologies within this sector.

Holistic analysis of the dynamic stability of the Southern Cameroon Interconnected Grid in contingency situations

The Southern Cameroon Interconnected Network (SIG) is depicted as a large-scale power system that has shown significant instability due to a series of blackouts in recent years. These blackouts are primarily attributed to major disruptions in transmission lines and energy deficits between supply and demand. The imbalance between power supply and demand necessitates the grid to operate near its stability limits, increasing the risk of blackouts. The necessity of investigating the dynamics of SIG behavior in response to observed contingency situations serves as the primary motivation for this study. To achieve this objective, the SIG was modeled using saturated generators with ZIP static loads. Through Newton-Raphson based power flow calculations, voltage magnitude profiles of the grid were obtained for each generation scenario. An N-1 contingency consisting of a standard Newton-based continuation power flow (CPF) analysis has identified line 5-6 as the most frequent worst case of line outage. Additionally, a short-term transient analysis was conducted under three-phase short-circuit, line outage and generator outage scenarios. In the event of a short-circuit, the Mangombe-225 bus experienced the most significant impact. Concerning line outages, line 1-5 had the most adverse effect on the grid's frequency stability. However, generation outages had a lesser impact on frequency stability compared to other disturbances. Lastly, modal analysis revealed that the grid exhibited weak stability with a critical mode identified at a frequency of 4.0267 Hz, exceeding typical values. This underscores the necessity of damping the grid oscillations for enhanced stability.

Voltammetric determination of uric acid using a miniaturized platform based on screen-printed electrodes modified with platinum nanoparticles

Disposable and sensitive screen-printed carbon electrodes (SPCE) modified with multi-walled carbon nanotubes (MWCNT) and platinum nanoparticles (PtNPs) were constructed to analyse uric acid (UA) in biological samples using a miniaturized smartphone potentiostat system. Combining the nanomaterials with Nafion® yielded a stable dispersion that could be successfully used as an electroactive layer. Transmission electron microscopy (TEM) and energy dispersive scanning (EDS) were used to characterize the morphology of PtNPs. These revealed approximately spherical shapes with emission lines characteristics of platinum. Furthermore, PtNPs/MWCNT/SPCE film was characterized by scanning electron microscopy (SEM), which demonstrated the tubular characteristic of MWCNT distributed and covered by carbon black (CB) spheres present in the screen-printed ink. An enhanced current response was observed for UA voltammetric analysis, especially due to the synergism effect of PtNPs and MWCNT, which reduced the Rct value. The values of Dapp (1.6 × 10−6 cm−2 s−1) and kcat (2.76 × 103 mol−1 L/s) were determined for UA using the proposed sensor. The sensor displayed linear response for UA in the range from 5.0 × 10−6 mol/L to 6.9 × 10−4 mol/L, with a detection limit of 4.9 × 10−7 mol/L. Along with detectability, excellent performances were verified in terms of repeatability, anti-interference features, and analysis of UA in the biological samples.