1,414 research outputs found
Active and Fast Tunable Plasmonic Metamaterials
Active and Fast Tunable Plasmonic Metamaterials is a research development that has contributed to studying the interaction between light and matter, specifically focusing on the interaction between the electromagnetic field and free electrons in metals. This interaction can be stimulated by the electric component of light, leading to collective oscillations. In the field of nanotechnology, these phenomena have garnered significant interest due to their ability to enable the transmission of both optical signals and electric currents through the same thin metal structure. This presents an opportunity to connect the combined advantages of photonics and electronics within a single platform. This innovation gives rise to a new subfield of photonics known as plasmonic metamaterials.Plasmonic metamaterials are artificial engineering materials whose optical properties can be engineered to generate the desired response to an incident electromagnetic wave. They consist of subwavelength-scale structures which can be understood as the atoms in conventional materials. The collective response of a randomly or periodically ordered ensemble of such meta-atoms defines the properties of the metamaterials, which can be described in terms of parameters such as permittivity, permeability, refractive index, and impedance. At the interface between noble metal particles and dielectric media, collective oscillations of the free electrons in the metal particles can be resonantly excited, known as plasmon resonances. This work considered two plasmon resonances: localised surface plasmon resonances (LSPRs) and propagating surface plasmon polaritons (SPPs).The investigated plasmonic metamaterials, designed with specific structures, were considered for use in various applications, including telecommunications, information processing, sensing, industry, lighting, photovoltaic, metrology, and healthcare. The sample structures are manufactured using metal and dielectric materials as artificial composite materials. It can be used in the electromagnetic spectrum's visible and near-infrared wavelength range. Results obtained proved that artificial composite material can produce a thermal coherent emission at the mid-infrared wavelength range and enable active and fast-tunable optoelectronic devices. Therefore, this work focused on the integrated thermal infrared light source platforms for various applications such as thermal analysis, imaging, security, biosensing, and medical diagnosis. Enabled by Kirchhoff's law of thermal radiation, this work combined the concepts of material absorption with material emission. Hence, the results obtained proved that this approach enhances the overall performance of the active and fast-tunable plasmonic metamaterial in terms of with effortless and fast tunability. This work further considers the narrow line width of the coherent thermal emission, tunable emission, and angular tunable emission at the mid-infrared, which are achieved through plasmonic stacked grating structure (PSGs) and plasmonic infrared absorber structure (PIRAs).Three-dimensional (3D) plasmonic stacked gratings (PSGs) was used to create a tunable plasmonic metamaterial at optical wavelengths ranging from 3 m to 6 m, and from 6m to 9 m. These PSGs are made of a metallic grating with corrugations caused by narrow air openings, followed by a Bragg grating (BG). Additionally, this work demonstrated a thermal radiation source customised for the mid-infrared wavelength range of 3 μm to 5 μm. This source exhibits intriguing characteristics such as high emissivity, narrowband spectra, and sharp angular response capabilities. The proposed thermal emitter consists of a two-dimensional (2D) metallic grating on top of a one-dimensional dielectric BG.Results obtained presented a plasmonic infrared absorber (PIRA) graphene nanostructure designed for a wavelength range of 3 to 14 μm. It was observed and concluded that this wavelength range offers excellent opportunities for detection, especially when targeting gas molecules in the infrared atmospheric windows. The design framework is based on active plasmon control for subwavelength-scale infrared absorbers within the mid-infrared range of the electromagnetic spectrum. Furthermore, this design is useful for applications such as infrared microbolometers, infrared photodetectors, and photovoltaic cells.Finally, the observation and conclusion drawn for the sample of nanostructure used in this work, which consists of an artificial composite arrangement with plasmonic material, can contribute to a highly efficient mid-infrared light source with low power consumption, fast response emissions, and is a cost-effective structure
GAO Optimized Sliding Mode Based Reconfigurable Step Size Pb&O MPPT Controller With Grid Integrated EV Charging Station
The deployment of renewable energy sources has become more frequent in power system networks over the last few years. The prevalence of global warming and some catastrophic climate changes is rising, along with the demand for intricate transport systems, as a result of rapid growth in civilization and modernization in culture. To fight this environmental issue associated with vehicle transmission, almost every nation is promoting electric vehicles (EV). In this article, a novel method for developing a sliding mode maximum power point tracking (MPPT) controller for photovoltaic (PV) systems operating in rapidly varying atmospheric circumstances is put forward. Further, the standard Perturb and observe (Pb&O) algorithm’s variable step is driven by the best sliding mode controller (SLMC) gains, which are determined using the Genetic Algorithm (GAO). Additionally, a PI controller, a grid employing current controlling topology, and an effective charging station constructed with GAO-optimized Sliding Mode-based reconfigurable step size Pb&O as an MPPT controller are executed and tested in MATLAB/Simulink for optimal control of power in the EV charging station. The main contribution of this study is to enhance the created controller’s tracking performance to reach the maximum power point (MPP) with negligible oscillation, low overshoot, minimum ripple, and excellent speed in conditions of air turbulence that change quickly, as well as ensure continuity in supply to the EV. Furthermore, the developed system as a whole shows good efficacy compared with other existing systems reviewed in the literature. Finally, this proposed strategy ensures continuity of power supply to the charging station even in uncertain weather conditions, as grid integration also plays a vital role in the overall demand
Optical Filter Design for Daylight Outdoor Electroluminescence Imaging of PV Modules
This paper presents an advanced outdoor electroluminescence (EL) imaging system for inspecting solar photovoltaic (PV) modules under varying daylight conditions. EL imaging, known for its effectiveness in non-destructively detecting PV module defects, is enhanced through specialized optical filters. These filters, including a bandpass filter targeting EL emissions and a neutral density filter to reduce background light, significantly improve the system’s signal-to-noise ratio (SNR). The experimental results demonstrate the system’s enhanced performance, with superior clarity and detail in EL emissions, enabling precise defect localization and characterization at the cellular level. Notably, the system achieves an SNR improvement, with values consistently above two, outperforming previous systems and confirming its suitability for efficient solar PV maintenance and diagnostics. This research offers a flexible approach to optimizing EL imaging quality across various solar irradiance levels and angles, essential for improved PV module performance and reliability. The system effectively handles different PV module configurations, orientations, and types, including monofacial and bifacial arrays. It showcases robust imaging capabilities under high solar irradiance and different sun illumination levels, maintaining high-quality imaging due to its optimized filter design. Additionally, the system’s adaptability in detecting EL emissions from series-connected PV modules is highlighted, demonstrating its comprehensive evaluation capabilities for PV array performance
Optimization for Energy Management in the Community Microgrids
This thesis focuses on improving the energy management strategies for Community Microgrids (CMGs), which are expected to play a crucial role in the future smart grid. CMGs bring many benefits, including increased use of renewable energy, improved reliability, resiliency, and energy efficiency. An Energy Management System (EMS) is a key tool that helps in monitoring, controlling, and optimizing the operations of the CMG in a cost-effective manner. The EMS can include various functionalities like day-ahead generation scheduling, real-time scheduling, uncertainty management, and demand response programs.
Generation scheduling in a microgrid is a challenging optimization problem, especially due to the intermittent nature of renewable energy. The power balance constraint, which is the balance between energy demand and generation, is difficult to satisfy due to prediction errors in energy demand and generation. Real-time scheduling, which is based on a shorter prediction horizon, reduces these errors, but the impact of uncertainties cannot be completely eliminated. In regards to demand response programs, it is challenging to design an effective model that motivates customers to voluntarily participate while benefiting the system operator.
Mathematical optimization techniques have been widely used to solve power system problems, but their application is limited by the need for specific mathematical properties. Metaheuristic techniques, particularly Evolutionary Algorithms (EAs), have gained popularity for their ability to solve complex and non-linear problems. However, the traditional form of EAs may require significant computational effort for complex energy management problems in the CMG.
This thesis aims to enhance the existing methods of EMS in CMGs. Improved techniques are developed for day-ahead generation scheduling, multi-stage real-time scheduling, and demand response implementation. For generation scheduling, the performance of conventional EAs is improved through an efficient heuristic. A new multi-stage scheduling framework is proposed to minimize the impact of uncertainties in real-time operations. In regards to demand response, a memetic algorithm is proposed to solve an incentive-based scheme from the perspective of an aggregator, and a price-based demand response driven by dynamic price optimization is proposed to enhance the electric vehicle hosting capacity. The proposed methods are validated through extensive numerical experiments and comparison with state-of-the-art approaches. The results confirm the effectiveness of the proposed methods in improving energy management in CMGs
Hydrogen-powered refrigeration system for environmentally friendly transport and delivery in the food supply chain
Urban population and the trend towards online commerce leads to an increase in delivery solution in cities. The
growth of the transport sector is very harmful to the environment, being responsible for approximately 40% of
greenhouse gas emissions in the European Union. The problem is aggravated when transporting perishable
foodstuffs, as the vehicle propulsion engine (VPE) must power not only the vehicle but also the refrigeration unit.
This means that the VPE must be running continuously, both on the road and stationary (during delivery), as the
cold chain must be preserved. The result is costly (high fuel consumption) and harmful to the environment. At
present, refrigerated transport does not support full-electric solutions, due to the high energy consumption
required, which motivates the work presented in this article. It presents a turnkey solution of a hydrogenpowered
refrigeration system (HPRS) to be integrated into standard light trucks and vans for short-distance
food transport and delivery. The proposed solution combines an air-cooled polymer electrolyte membrane fuel
cell (PEMFC), a lithium-ion battery and low-weight pressurised hydrogen cylinders to minimise cost and increase
autonomy and energy density. In addition, for its implementation and integration, all the acquisition, power and
control electronics necessary for its correct management have been developed. Similarly, an energy management
system (EMS) has been developed to ensure continuity and safety in the operation of the electrical system during
the working day, while maximizing both the available output power and lifetime of the PEMFC. Experimental
results on a real refrigerated light truck provide more than 4 h of autonomy in intensive intercity driving profiles,
which can be increased, if necessary, by simply increasing the pressure of the stored hydrogen from the current
200 bar to whatever is required. The correct operation of the entire HPRS has been experimentally validated in
terms of functionality, autonomy and safety; with fuel savings of more than 10% and more than 3650 kg of CO2/
year avoided.This work is a contribution of the two following Projects: “H2Integration& Control. Integration and Control of a hydrogen-based pilot plant in residential applications for energy supply”, Ref. PID2020-116616RB-C31 supported by the Spanish State Program of R + D + I Oriented to the Challenges of Society; and “SALTES: Smartgrid with reconfigurable Architecture for testing controL Techniques and Energy Storage priority contaminant waste”, Ref. P20-00730 supported by
Andalusian Regional Program of R + D + I. Funding for open access charge: Universidad de Huelva/CBUA
RF Wireless Power and Data Transfer : Experiment-driven Analysis and Waveform Design
The brisk deployment of the fifth generation (5G) mobile technology across the globe has accelerated the adoption of Internet of Things (IoT) networks. While 5G provides the necessary bandwidth and latency to connect the trillions of IoT sensors to the internet, the challenge of powering such a multitude of sensors with a replenishable energy source remains. Far-field radio frequency (RF) wireless power transfer (WPT) is a promising technology to address this issue. Conventionally, the RF WPT concepts have been deemed inadequate to deliver wireless power due to the undeniably huge over-the-air propagation losses. Nonetheless, the radical decline in the energy requirement of simple sensing and computing devices over the last few decades has rekindled the interest in RF WPT as a feasible solution for wireless power delivery to IoT sensors.
The primary goal in any RF WPT system is to maximize the harvested direct current (DC) power from the minuscule incident RF power. As a result, optimizing the receiver power efficiency is pivotal for an RF WPT system. On similar lines, it is essential to minimize the power losses at the transmitter in order to achieve a sustainable and economically viable RF WPT system. In this regard, this thesis explores the system-level study of an RF WPT system using a digital radio transmitter for applications where alternative analog transmit circuits are impractical. A prototype test-bed comprising low-cost software-defined radio (SDR) transmitter and an off-the-shelf RF energy-harvesting (EH) receiver is developed to experimentally analyze the impact of clipping and nonlinear amplification at the digital radio transmitter on digital baseband waveform. The use of an SDR allows leveraging the test-bed for the research on RF simultaneous wireless information and power transfer (SWIPT); the true potential of this technology can be realized by utilizing the RF spectrum to transport data and power together. The experimental results indicate that a digital radio severely distorts high peak-to-average power ratio (PAPR) signals, thereby reducing their average output power and rendering them futile for RF WPT.
On similar lines, another test-bed is developed to assess the impact of different waveforms, input impedance mismatch, incident RF power, and load on the receiver power efficiency of an RF WPT system. The experimental results provide the foundation and notion to develop a novel mathematical model for an RF EH receiver. The parametric model relates the harvested DC power to the power distribution of the envelope signal of the incident waveform, which is characterized by the amplitude, phase and frequency of the baseband waveform. The novel receiver model is independent of the receiver circuit’s matching network, rectifier configuration, number of diodes, load as well as input frequency. The efficacy of the model in accurately predicting the output DC power for any given power-level distribution is verified experimentally.
Since the novel receiver model associates the output DC power to the parameters of the incident waveform, it is further leveraged to design optimal transmit wave-forms for RF WPT and SWIPT. The optimization problem reveals that a constant envelope signal with varying duty cycle is optimal for maximizing the harvested DC power. Consequently, a pulsed RF waveform is optimal for RF WPT, whereas a continuous phase modulated pulsed RF signal is suitable for RF SWIPT. The superior WPT performance of pulsed RF waveforms over multisine signals is demonstrated experimentally. Similarly, the pulsed phase-shift keying (PSK) signals exhibit superior receiver power efficiency than other communication signals. Nonetheless, varying the duty-cycle of pulsed PSK waveform leads to an efficiency—throughput trade-off in RF SWIPT.
Finally, the SDR test-bed is used to evaluate the overall end-to-end power efficiency of different digital baseband waveforms through wireless measurements. The results indicate a 4-PSK modulated signal to be suitable for RF WPT considering the overall power efficiency of the system. The corresponding transmitter, channel and receiver power efficiencies are evaluated as well. The results demonstrate the transmitter power efficiency to be lower than the receiver power efficiency
Magnetic Integration Techniques for Resonant Converters
This thesis sets out a series of new transformer topologies for magnetic integration in different resonant converters. Resonant converters like LLC converters require a high number of magnetic components, leading to low power density and high cost. These magnetic components can usually be integrated into a single transformer to increase power density, efficiency, manufacturing simplicity and to reduce cost. This strategy is known as integrated transformer (IT). The work described in this thesis has sought to deliver improvements in implementing this strategy.
The benefits of resonant converters compared to pulse-width-modulated (PWM) converters are discussed. To show the drawbacks of PWM converters, two hard-switched DC-DC converters and two soft-switched DC-DC converters using state-of-the-art wide bandgap (WBG) gallium nitride devices are constructed and investigated.
The LLC resonant converter is fully discussed for unidirectional and bidirectional applications. The different techniques for magnetic integration that can be applied to the LLC resonant converter are reviewed. Amongst these techniques, the inserted-shunt integrated transformers, which have gained popularity recently, are made a focus of the thesis.
In general, the important challenges concerning the inserted-shunt integrated transformers are the need for bespoke material for the shunt, unwanted high leakage inductance on the secondary side, and that integrated magnetics are not usually suitable for bidirectional converters such as CLLLC converters.
Two new topologies (IT1 and IT2) for inserted-shunt integrated transformers are presented that do not need bespoke material for the shunt and can be constructed from materials available commercially in large and small quantities. However, the manufacturing of these proposed topologies is challenging since magnetic shunts are made by joining several smaller magnetic pieces to form a segmented piece.
A further new topology (IT3) is presented that not only does not need bespoke material for the shunt but also benefits from simple manufacturing. However, inserted-shunt integrated transformer, including all three proposed topologies (IT1-IT3), still suffer from increased leakage inductance on the secondary side, leading the control and design of the resonant converters to difficulty.
Another topology (IT4) is therefore proposed that can be constructed easily with commercially available materials and does not increase the leakage inductance on the secondary side. However, all four proposed topologies (IT1-IT4) and other topologies with an inserted-shunt are not suitable for use in bidirectional LLC-type resonant converters when different primary and secondary leakage inductances are needed, such as where variable gain is required.
Finally, a topology (IT5) is proposed that can be used in bidirectional LLC-type converters while it still benefits from simple manufacturing and using commercially available materials.
All the proposed topologies (IT1-IT5) are discussed in detail and their design guidelines and modelling are provided. The theoretical analysis is confirmed by finite-element (FEM) analysis and experimental results.
A unidirectional LLC resonant converter and a bidirectional CLLLC resonant converter are implemented to investigate the performance of the proposed integrated transformers (IT1-IT5) in practice. It is shown that the converters can operate properly while all their magnetic components are integrated into the proposed transformers
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Evaluating the intention to use Industry 5.0 (I5.0) drones for cleaner production in Sustainable Food Supply Chains:an emerging economy context
YesPurpose – The purpose of this study is to evaluate food supply chain stakeholders’ intention to use Industry 5.0 (I5.0) drones for cleaner production in food supply chains.
Design/methodology/approach – We used a quantitative research design and collected data using an online survey administered to a sample of 264 food supply chain stakeholders in Nigeria. The partial least square structural equation model (PLS-SEM) was conducted to assess the research’s hypothesised relationships.
Findings – We provide empirical evidence to support the contributions of I5.0 drones for cleaner production. Our findings showed that food supply chain stakeholders are more concerned with the use of I5.0 drones in specific operations such as reducing plant diseases which invariably enhances cleaner production. However, there is less inclination to drones adoption if the aim was pollution reduction, predicting seasonal output and addressing workers health and safety challenges. Our findings outline the need for awareness to promote the use of drones for addressing workers hazard challenges and knowledge transfer on the potentials of I5.0 in emerging economies.
Originality – This is the first study to address I5.0 drones' adoption using a sustainability model. We contribute to existing literature by extending the sustainability model to identify the contributions of drones use in promoting cleaner production through addressing specific system operations. This study addresses the gap by augmenting a sustainability model, suggesting that technology adoption for sustainability is motivated by curbing challenges categorised as drivers and mediators
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