Energy Efficient Transmission Research Articles

Technology Selection of High-Voltage Offshore Substations Based on Artificial Intelligence

This paper proposes an automated approach to the technology selection of High-Voltage Alternating Current (HVAC) Offshore Substations (OHVS) for the integration of Oil & Gas (O&G) production and Offshore Wind Farms (OWF) based on Artificial Intelligence (AI) techniques. Due to the complex regulatory landscape and project diversity, this is enacted via a cost decision-model which was developed based on Knowledge-Based Systems (KBS) and incorporated into an optioneering software named Transmission Optioneering Model (TOM). Equipped with an interactive dashboard, it uses detailed transmission and cost models, as well as a technological and commercial benchmarking of offshore projects to provide a standardized selection approach to OHVS design. By automating this process, the deployment of a technically sound and cost-effective connection in an interactive sandbox environment is streamlined. The decision-model takes as primary inputs the power rating requirements and the distance of the offshore target site and tests multiple voltage/rating configurations and associated costs. The output is then the most technically and economically efficient interconnection setup. Since the TOM process relies on equivalent models and on a broad range of different projects, it is manufacturer-agnostic and can be used for virtually any site as a method that ensures both energy transmission and economic efficiency.

A Novel Energy-Efficient Routing Protocol for Industrial WSN Using Hybrid Coot-Ls Algorithm with LSTM-Based Dom Prediction

In industrial Wireless Sensor Networks (WSNs), energy efficiency and reliable data transmission are critical challenges that need to be addressed to ensure sustainable and robust network operations. This paper proposes a novel energy-efficient routing protocol that integrates a Hybrid COOT-LS (Coot- Levy Search) algorithm with Long Short-Term Memory (LSTM)-based Dominant Object Motion (DOM) prediction. The routing protocol leverages the strengths of Hybrid Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) to enhance routing efficiency and reduce energy consumption. The Hybrid PSO and ACO algorithms are employed to optimize routing paths by balancing exploration and exploitation, considering multiple factors such as energy levels, node distance, and reliability. The COOT-LS algorithm further refines these paths by incorporating a Levy flight mechanism to enhance the search process. Additionally, the LSTM-based DOM prediction provides accurate forecasts of network conditions, enabling dynamic adjustments to routing strategies in real time. Simulation results demonstrate that the proposed protocol significantly improves network lifetime, reduces energy consumption, and enhances data transmission reliability compared to traditional routing protocols. This approach provides a robust and scalable solution for industrial WSN applications, ensuring efficient and reliable network performance in dynamic and complex industrial environments.

An Energy-Balance Clustering Routing Protocol for Intra-Body Wireless Nanosensor Networks

Aims and Background: Numerous sensor nodes spread out across the surveillance region form the Wireless-Sensor Network (WSN), a smart, self-organizing network. Since the lumps can typically only be motorized by batteries, creating a WSN while maintaining an optimal energy balance and extending the network's lifetime is the biggest issue. Methods: A novel network architecture that integrates nanotechnology with sensor networks is known as a Wireless-NanoSensor-Network(WNSN). A new area of focus in research is intra-bodyiWNSNs, which are WNSNs with promising potential applications in biomedicine, damage detection, and intra-body health monitoring. We suggest an energy-balance-clustering-routing protocol (EBCR) for iSN nodes that have limited energy storage, short communication range, and low computation and processing capabilities. The protocol uses a novel hierarchical clustering approach to lessen the communication burden on nano-nodes. Results: Cluster nano-nodes can use one-hop routing to send data directly to the Cluster-Head(CH) nodes, and the CH-nodes can utilize multi-hop routing to send data to the nano control node. In addition, selecting the next hop node to minimize energy usage while guaranteeing successful data packet delivery involves balancing distance and channel capacity. The protocol's strengths in energy efficiency, network-lifetime extension, and data-packet transmission success rate were highlighted by the simulation results. Conclusion: It is clear that the EBCR protocol is a viable option for iWNSNs' routing system.

Efficient fiber-inspection and certification method for optical-circuit-switched datacenter networks

Datacenter networks (DCNs) consisting of optical circuit switches (OCSs) have been considered as a promising solution to dramatically improve their transmission capacity, energy efficiency, and communication latency. To scale optical-circuit-switched DCNs (OCS DCNs), hierarchical OCSs with tens of thousands of optical fibers need to be installed, and they should be inspected before starting datacenter operations. Since traditional DCNs consist of electrical-packet switches (EPSs), the condition and cabling of fibers can be inspected easily by probing neighboring EPSs. However, OCS networks cannot be inspected in the same manner because OCSs cannot transmit and receive probe signals. Thus, we have had to attach and detach a light source and power meter (LSPM) to every switch for probing all the fibers, which takes weeks. This paper proposes an efficient method for inspecting and certifying fibers in an entire DCN without repeating LSPM reattachment. Our method is based on (1) theories on quickly estimating the fiber condition on the basis of the intensity of received probe signals, (2) the maximum allowable loss of each fiber derived from the transceiver budget used in operations, and (3) an algorithm that reduces the number of probes needed. The results from an extensive numerical evaluation indicate that our method inspected a DCN with 18,432 fibers in at most a day, whereas a baseline method involving repeated LSPM reattachment would take more than a week. We also confirmed that our method never produced false negatives and false positives under practical network conditions.

Development of an Imaging Spectrometer with a High Signal-to-Noise Ratio Based on High Energy Transmission Efficiency for Soil Organic Matter Detection.

Hyperspectral detection of the change rate of organic matter content in agricultural remote sensing requires a high signal-to-noise ratio (SNR). However, due to the large number and efficiency limitation of the components, it is difficult to improve the SNR. This study uses high-efficiency convex grating with a diffraction efficiency exceeding 50% across the 360-850 nm range, a back-illuminated Complementary Metal Oxide Semiconductor (CMOS) detector with a 95% efficiency in peak wavelength, and silver-coated mirrors to develop an imaging spectrometer for detecting soil organic matter (SOM). The designed system meets the spectral resolution of 10 nm in the 360-850 nm range and achieves a swath of 100 km and a spatial resolution of 100 m at an orbital height of 648.2 km. This study also uses the basic structure of Offner with fewer components in the design and sets the mirrors of the Offner structure to have the same sphere, which can achieve the rapid adjustment of the co-standard. This study performs a theoretical analysis of the developed Offner imaging spectrometer based on the classical Rowland circular structure, with a 21.8 mm slit length; simulates its capacity for suppressing the +2nd-order diffraction stray light with the filter; and analyzes the imaging quality after meeting the tolerance requirements, which is combined with the surface shape characteristics of the high-efficiency grating. After this test, the grating has a diffraction efficiency above 50%, and the silver-coated mirrors have a reflection value above 95% on average. Finally, the laboratory tests show that the SNR over the waveband exceeds 300 and reaches 800 at 550 nm, which is higher than some current instruments in orbit for soil observation. The proposed imaging spectrometer has a spectral resolution of 10 nm, and its modulation transfer function (MTF) is greater than 0.23 at the Nyquist frequency, making it suitable for remote sensing observation of SOM change rate. The manufacture of such a high-efficiency broadband grating and the development of the proposed instrument with high energy transmission efficiency can provide a feasible technical solution for observing faint targets with a high SNR.

The impact of energy (Electricity) losses on load capacity factor: A dynamic ARDL-based evidence from Pakistan

The energy-environment interplay has raised significant concerns among policymakers and experts, with the global shift towards renewable energy being hailed as a key solution to reduce pollution emissions. However, in addition to energy production, the efficient transmission and distribution of electricity is also important which also poses considerable challenges to environmental sustainability. This study aims to investigate the effect of electricity losses on environmental sustainability measured by load capacity factor (LCF). This study uses the DARDL (DARDL) method and Kernel-based Regularized Least Squares (KRLS) to analyze the influence of electricity losses, foreign direct investment (FDI), economic growth, and industrial output on LCF in Pakistan from 1981 to 2022. The electricity losses significantly undermine environmental sustainability by reducing LCF. However, FDI positively influences LCF, but economic growth and industrial output exert a detrimental effect. Additionally, the study observes that both positive and negative counterfactual 10 % shocks in electricity losses result in negative and positive impacts on LCF. Whereas, 10 % positive counterfactual shocks in FDI positively affect LCF. KRLS analysis confirms the robustness of the DARDL estimates. The study underscores that efficient energy transmission and distribution is pivotal in safeguarding environmental sustainability.

Secure energy efficiency maximization for joint ITS and IRS assisted satellite downlink communications

AbstractSatellite communications (SatCom) have been viewed as a promising technique to achieve ubiquitous global coverage in next‐generation wireless systems. This article investigates the secure energy efficient downlink transmission for SatCom where an intelligent transmissive surface‐aided transmitter is deployed at the satellite to perform energy efficient beamforming and an intelligent reflecting surface as well as a cooperative jammer are deployed on the ground to enhance the secure performance. The aim is to maximize the secure energy efficiency by jointly designing ITS beamforming, IRS phase shift, jammer precoding vector, and transmit power allocation. To develop a low‐complexity solution,first, an approximated concave lower bound of the non‐concave objective function is derived by utilizing Dinkelbach's method and a novel successive convex approximation technique. Then the reformulated problem is decoupled using alternating optimization algorithm and the subproblems are solved by adopting Riemannian manifold optimization, element‐wise block coordinate descent, Lagrange dual method and Karush–Kuhn–Tucker conditions. At last, simulation results demonstrate the effectiveness of the proposed scheme.

An energy-aware cluster-based routing in the Internet of things using particle swarm optimization algorithm and fuzzy clustering

The effectiveness and longevity of IoT infrastructures heavily depend on the limitations posed by communication, multi-hop data transfers, and the inherent difficulties of wireless links. In dealing with these challenges, routing, and data transmission procedures are critical. Among the fundamental concerns are the attainment of energy efficiency and an ideal distribution of loads among sensing devices, given the restricted energy resources at the disposal of IoT devices. To meet these challenges, the present research suggests a novel hybrid energy-aware IoT routing approach that mixes the Particle Swarm Optimization (PSO) algorithm and fuzzy clustering. The approach begins with a fuzzy clustering algorithm to initially group sensor nodes by their geographical location and assign them to clusters determined by a certain probability. The proposed method includes a fitness function considering energy consumption and distance factors. This feature guides the optimization process and aims to balance energy efficiency and data transmission distance. The hierarchical topology uses the advanced PSO algorithm to identify the cluster head nodes. The MATLAB simulator shows that our method outperforms previous approaches. Various metrics have demonstrated significant improvements over DEEC and LEACH. The method reduces energy consumption by 52% and 16%, improves throughput by 112% and 10%, increases packet delivery rates by 83% and 15%, and extends the network lifespan by 48% and 27%, respectively, compared to DEEC and LEACH approaches.

Energy Efficient and Reliable High Quality Video Transmission Architecture for Wireless Sensor Networks

Energy Efficient and Reliable High Quality Video Transmission Architecture for Wireless Sensor Networks

Design and Construction of a Multipole Electric Motor Using an Axial Flux Configuration

In the transportation industry, the use of renewable energies has been implemented in conjunction with the development of higher-power electric motors and, consequently, the development of intelligent control systems for torque and speed control. Currently, the coupling between both systems is being developed through mechanical systems, affecting the efficient transmission of energy and the useful life of the components. On the other hand, new configurations of electric motors are being developed, such as axial flux motors (AFM), because these can be coupled directly without a mechanical coupling, given their characteristics of high torque at low speeds. In the present work, an innovative design of a multipole axial flux motor (MAFM) is introduced. General criteria for the design and construction are presented considering the geometry in axial flux and permanent magnets. The performance of the system is evaluated through finite element magnetic simulations (FEMM) and compared with experimental measurements of the developed prototype; confirming the effectiveness of the design, obtaining torques of up to 1.784 Nm without extra mechanical couplings and maximum speed regulation errors of 8.43%. The motor was controlled by a digital pole switching system whit six control mode, applied to a permanent magnet MFA for speed and torque control at constant speed. This control can be extended to conventional radial flux electric motor configurations and intelligent traction applications, based on torque demand.

Energy efficient reliable data transmission for optimizing IoT data transmission in smart city

The rapid proliferation of the internet of things (IoT) technology has significantly transformed urban landscapes, giving rise to smart city frameworks that leverage interconnected devices for enhanced efficiency and functionality. In these environments, vast amounts of data are generated by diverse sensors and devices, necessitating advanced strategies for effective data collection and transmission. This paper introduces a novel approach to address data collection and transmission challenges in IoT-enabled smart city frameworks. The proposed design integrates IoT-Cloud for efficient data collection and employs the energy efficient reliable data transmission (EERDT) model, optimizing IoT data transmission. The enhanced dragonfly routing algorithm, incorporating the firefly algorithm, enhances data routing efficiency. Experimental results demonstrate EERDT's superiority over energy-aware iot-routing (EAIR) and location-centric energy-harvesting aware-routing (LCEHAR), revealing significant improvements in communication overhead, data processing latency, and network lifetime. The EERDT exhibits substantial reductions in communication overhead, enhancing overall network performance. The EERDT model showcases lower data processing latency and energy consumption, highlighting its potential for resource-efficient IoT data transmission. This work contributes an innovative solution for smart city IoT networks, emphasizing performance enhancements and resource efficiency.

Influence of contact characteristics of joint surface on vibration performance of the giant magnetostrictive transducer

The giant magnetostrictive transducer is a transducer device that realizes magneto-mechanical energy conversion. Each mechanical component is connected by the joint surface to realize the transmission of ultrasonic vibration energy. To ensure the efficient transmission of energy, the influence of the contact characteristics of the joint surface on the output stability of the transducer is studied. According to the contact conditions between the mechanical joint surfaces of the giant magnetostrictive ultrasonic transducer (GMUT), the key factors affecting the mechanical vibration performance of the ultrasonic system are obtained by analyzing the vibration transmission characteristics of the joint surfaces. The influence of different joint surface contact characteristics (JSCT) on the amplitude–frequency curve of the transducer is analyzed by the ANSYS software. Simulations and experiments have been conducted to verify the predicted results. As the preload force increases, the natural frequency of the transducer increases, but the growth rate decreases. The natural frequency of the double-rod GMUT with a small joint surface area is slightly higher in the optimal output mode shape, while its amplitude is significantly larger. The optimal prestress for the GMUT with different-sized joint surfaces is 3–5 MPa. This paper acquires the JSCT under a high-frequency vibration condition, reveals the influence of the joint surface on the mechanical output performance of the GMUT, and can provide a theoretical basis for the design and analysis of the rotary ultrasonic vibration processing system.

Non-smooth nonlocal mechanical diode

In this paper, we proposed a new mechanical diode with non-smooth and nonlocal elastic, which support a backflow of the input mechanical energy. It is composed of a nonlinear converter connecting with nonlocal bilinear springs and linear phononic crystal. The asymmetrical stiffness of bilinear springs can be utilized to periodically modulate the stiffness of converter, generate non-reciprocal propagation of mechanical waves, thereby decompose the excitation frequency into multiple sub-bands. Utilizing this characteristic of converter, during the forward propagation of mechanical diodes, it is possible to effectively surpass the cutoff frequency of phononic crystals, ensuring higher energy transmission efficiency and achieving wideband performance of mechanical diodes. Nonlocal connections induce a roton-like dispersion in the wave propagation, resulting in negative group velocities and partial energy backflow. The Runge-Kutta method is utilized to simulate wave propagation and verified by experimental. It is shown that the low-frequency impinging wave is rectified and nearly 100% contrast ratio is observed. Our work provide a new platform for mechanical wave manipulation and energy harvesting.

Enhancement of transmission line parameters for the supply of energy in the Rivers state local government area of Obio Akpor

Efficient energy transmission is crucial for meeting the growing demand for electricity, particularly in urban and rural areas. In the Rivers State Local Government Area of Obio Akpor, Nigeria, ensuring reliable power supply is essential for supporting economic development and improving quality of life. However, challenges such as transmission line losses, voltage fluctuations, and inadequate infrastructure hinder the effective distribution of energy in the region. This article presents a comprehensive study on enhancing transmission line parameters to improve energy supply in Obio Akpor. Through field measurements, data analysis, and simulation studies, the performance of existing transmission lines is evaluated, and strategies for enhancing efficiency and reliability are proposed. The literature review explores previous research on transmission line optimization, emphasizing factors such as conductor material, line design, and insulation to minimize losses and maximize power transfer capability. Materials and methods encompass data collection, including impedance measurements, voltage profiles, and load characteristics, followed by computer simulations to assess proposed enhancements.

Active ballistic orbital transport in Ni/Pt heterostructure

Orbital current, defined as the orbital character of Bloch states in solids, can travel with larger coherence length through a broader range of materials than its spin counterpart, facilitating a robust, higher density and energy efficient information transmission. Hence, active control of orbital transport plays a pivotal role in the progress of the evolving field of quantum information technology. Unlike spin angular momentum, orbital angular momentum couples to phonon angular momentum efficiently via orbital-crystal momentum (L-k) coupling, allowing us to control orbital transport through crystal field potential mediated angular momentum transfer. Here, leveraging the orbital dependant efficient L-k coupling, we have experimentally demonstrated the active control of orbital current velocity in Ni/Pt heterostructure. We observe terahertz emission from Ni/Pt heterostructure via long-range ballistic orbital transport, as evidenced by the delay, and chirping in the emitted THz pulse correlating with increased Pt thickness. Additionally, we also have identified a critical energy density required to overcome collisions in orbital transport, enabling a swifter flow of orbital current. Femtosecond light driven active control of the ballistic orbital transport lays the foundation for the development of dynamic optorbitronics for transmitting information over extended distance.

Study of operation mode and breakdown characteristics for multi-stage gas switch

Multi-stage gas switches (MSGSs) are widely used in megavolt pulsed power systems due to their advantages of high withstand voltage, fast establishing time and relatively high operating frequency. Multiple operation modes, which are induced by the different breakdown sequences at each stage, are found to affect the breakdown characteristics of the gas switch. Based on the theoretical analysis of the working principle, the classification of the operation mode and the factors determining the operation mode of the MSGS are proposed. Methods for investigating the output waveform for MSGS are established by simulating lumped parameters and studying the breakdown time sequence of individual stages. In comparison with the intended mode of operation, the disadvantages of the unintended modes of operation for MSGS, including error-breakdown and non-triggering mode, are revealed. For unintended modes, the distortion of the output waveform, which determines the efficiency of energy transmission through the switch and the increased delay time jitter, which determines the synchronization of the gas switch, are further investigated. The possibility of non-triggering and its mechanism on surface flashovers induced by drifting electrons are also analyzed. Based on this study, design principles and methods are proposed to ensure the intended operation of the MSGS.

Joint subchannel power allocation for downlink NOMA systems based on quantum carnivorous plant algorithm

Currently, most existing research on non-orthogonal multiple access (NOMA) systems converts power allocation into two independent procedures, i.e., inter-subchannel power allocation and intra-subchannel power allocation. However, improper inter-subchannel power allocation will adversely affect the power allocation process of intra-subchannel. If the power allocations of inter-subchannel and intra-subchannel are optimized simultaneously, it usually needs high computational complexity, and is hard to obtain an optimal solution. To tackle this issue, this paper studies the joint subchannel power allocation for NOMA systems and proposes a new intelligent algorithm called quantum carnivorous plant algorithm (QCPA) for simultaneously optimizing inter-subchannel and intra-subchannel power allocations. Analysis of the convergence of QCPA verified its superior performance on the test functions. By utilizing the optimal solution obtained by QCPA as the power allocation scheme, energy efficiency and sum transmission rate in NOMA systems are significantly increased compared to existing traditional power allocation methods. The results above demonstrate that QCPA effectively addresses test functions and the power allocation problem for NOMA. QCPA possesses favorable convergence in comparison to other comparison algorithms and methods.

Flexible Ultrasonic‐Induced Wireless Energy Conversion Technology in Implantable Biomedicine

AbstractNumerous associated challenges arise with the advancement and continuous improvement of implantable medical devices, such as the frequent requirement for battery replacement. The flexible ultrasonic‐induced wireless energy conversion (UWEC) technology has garnered significant interest due to its superior energy transmission efficiency, safety, and biocompatibility compared to traditional electromagnetic wireless energy conversion technology. This paper provides a comprehensive review of the recent advancements in two types of flexible UWEC technologies, triboelectric nanogenerators, and piezoelectret nanogenerators, with a focus on their applications in implantable medical treatments. First, the energy conversion principles and general materials of flexible UWEC are presented. Then, the research and application of flexible UWEC devices are introduced in detail based on their medical functions. At the end of this review, perspectives and opportunities are discussed.

Evaluating battery electric vehicle usage in the EU: A comparative study based on member state energy mixes

The transport sector is undergoing a major transformation, as battery electric vehicles (BEV) are gaining ground. Therefore, assessing the sustainability aspects of their use is crucial to obtaining a clear picture of the sector. This article aims to meet this requirement by using European Union (EU) data for the period 2011 to 2021 and focuses not only on EU-27 aggregates but also on each member state separately. For the evaluation, a well-to-wheel (WTW) method was used to calculate two parameters: energy-specific CO2 emissions (ε) and total efficiency of energy conversions, transmission, and battery (ηtotal). For these values, the annual electricity mixes of the countries were tracked in 5 + 1 categories (combined cycle gas turbine (CCGT), thermal power plant, biofuels, nuclear power plant (NPP), renewables, and imports). The calculated results were illustrated by sustainability matrices describing the former and current positions of the countries. The EU-27 aggregate achieved a 0.04 increase (from 0.37 to 0.41) in total efficiency and a 29 gCO2/MJmotion decrease (from 113 to 84 gCO2/MJmotion) during the period. This ε value for 2021 was around half the world average. However, very significant differences were identified between member states, which are also assessed in the article with special emphases on the five most populated EU countries (Germany, France, Italy, Spain, and Poland).

Energy Efficient Transmission Strategy for Mobile Edge Computing Network in UAV-Based Patrol Inspection System

Energy Efficient Transmission Strategy for Mobile Edge Computing Network in UAV-Based Patrol Inspection System