High Power Utilization Research Articles

Numerical Study of Sputter Deposited Ultra-Low Loaded Effective Platinum Electrocatalyst Utilization in Proton Exchange Membrane Fuel Cell

High Platinum loading levels in fuel cells may ensure better durability and catalytic activity but increases fuel cells’ cost, thereby hindering large-scale commercialization. The use of non-precious catalysts may seem like a lucrative solution, but they cannot substitute platinum completely. Hence, the focus should also be given to alternate fabrication methods of the catalyst layer that will achieve ultra-low platinum loadings. Some of the methods are modified thin film method, electrodeposition, sputter deposition method, dual ion beam assisted deposition, and electroless deposition. Nano carbons as catalyst support can also be given priority as they aid the catalyst with mechanical properties. Each method is compared, reflecting the inherent advantages and disadvantages. Finally, the sputter deposition method was chosen as the most promising method in the current state of technology and research. A computational fluid dynamics simulation of a fuel cell using the sputter deposition method was performed which showed high power utilization thereby validating the benefits of the method.

Intelligent Resource Allocation Using an Artificial Ecosystem Optimizer with Deep Learning on UAV Networks

An Unmanned Aerial Vehicle (UAV)-based cellular network over a millimeter wave (mmWave) frequency band addresses the necessities of flexible coverage and high data rate in the next-generation network. But, the use of a wide range of antennas and higher propagation loss in mmWave networks results in high power utilization and UAVs are limited by low-capacity onboard batteries. To cut down the energy cost of UAV-aided mmWave networks, Energy Harvesting (EH) is a promising solution. But, it is a challenge to sustain strong connectivity in UAV-based terrestrial cellular networks due to the random nature of renewable energy. With this motivation, this article introduces an intelligent resource allocation using an artificial ecosystem optimizer with a deep learning (IRA-AEODL) technique on UAV networks. The presented IRA-AEODL technique aims to effectually allot the resources in wireless UAV networks. In this case, the IRA-AEODL technique focuses on the maximization of system utility over all users, combined user association, energy scheduling, and trajectory design. To optimally allocate the UAV policies, the stacked sparse autoencoder (SSAE) model is used in the UAV networks. For the hyperparameter tuning process, the AEO algorithm is used for enhancing the performance of the SSAE model. The experimental results of the IRA-AEODL technique are examined under different aspects and the outcomes stated the improved performance of the IRA-AEODL approach over recent state of art approaches.

Prospective study of a novel heat pump system with solar energy spectral beam splitting

Renewable solar energy as a resource for carbon emissions reduction, its application and promotion are hindered by low energy utilization efficiency. Photovoltaic modules mainly convert solar energy into electricity only in the high-frequency spectrum band. In order to achieve a high coefficient of performance, a novel heat pump system with solar energy spectral beam splitting was developed by matching the energy grade and heat pump cycle operating conditions. This also addresses the issue that the conventional heat pump system cannot supply heat efficiently and stably in the cold region of North China. Theoretical investigations were carried out on the distribution of parameters of energy load and efficiency. Compared with conventional PV modules, solar energy utilization with spectral beam splitting, which divides solar energy into the low-frequency spectrum for thermal energy collection and the high-frequency range for power generation, ensures high power production efficiency and utilization efficiency by the cascade thermal and electric energy exploitation in the proposed novel heat pump system. Partial thermal energy is used to provide the hot water, and the rest is upgraded by an ejector-based heat pump system to meet the space heating requirements. Therefore, the novel heat pump system achieves the combined supply of space heating, hot water, and electricity with high solar energy utilization efficiency through active energy conversion and thermal energy recovery. The goal of creating a structure with zero electric power consumption appears promising. When compared to the typical single PV system's (30.7%) efficiency, the suggested system's overall energy usage efficiency (up to 81.7%) is noticeably higher. In extreme cold areas, the performance superiority of the novel system is more prominent.

FPGA-based PPM Modulation System Design

As a widely used modulation technique in the field of communication, PPM modulation techniques have the advantages of high interference immunity, simple coding and high-power utilization, and are often applied in practical scenarios. PPM modulation techniques can be divided into three categories. single pulse position modulation, differential pulse position modulation and multi pulse position modulation. In different application scenarios, different kinds of pulse position modulation methods should be selected for modulation. In this paper, the frame structures of these three types of pulse position modulation are discussed using the Verilog language based on FPGA, the corresponding mapping relationships for each type of pulse position modulation are given, and the design and performance of these three types of pulse position modulation demodulation systems are compared.

Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction

In a world of connectivity empowered by the advancement of the Internet of Things (IoT), an infinite number of data streams have emerged. Thus, data stream clustering is crucial for extracting hidden knowledge and data mining. Various data stream clustering methods have lately been introduced. Yet, the majority of such algorithms are affected by the curse of high dimensionality. Lately, a fully online buffer-based clustering algorithm for handling evolving data streams (BOCEDS) was developed. Similarly to other existing density-based clustering methods, BOCEDS is not capable of handling high-dimensional data and has high computational power and high memory utilization. This paper introduces an Entropy Window Reduction (EWR) algorithm, which is an improved version of the BOCEDS technique. EWR is a fully online clustering technique for handling high-dimensional data streams using feature ranking and sorting. This process is accomplished by calculating the entropy of specific features with respect to the time window. The findings of the experiments are compared to the outcomes of BOCEDS, CEDAS, and MuDi-Stream algorithms. The outcomes indicate that the EWR algorithm outperformed the baseline clustering algorithms. The results are demonstrated using the KDDCup’99 dataset in terms of quality and complexity evaluation on the average of F-Measures, Jaccard Index, Fowlkes–Mallows index, Purity, and Rand Index as well as the memory usage and computational power with 88%, 66%, 81%, 100%, and 66%, respectively. The results also show low memory usage and computing power in comparison with the baseline algorithms.

An Energy-Efficient and Blockchain-Integrated Software Defined Network for the Industrial Internet of Things.

The number of unsecured and portable Internet of Things (IoT) devices in the smart industry is growing exponentially. A diversity of centralized and distributed platforms have been implemented to defend against security attacks; however, these platforms are insecure because of their low storage capacities, high power utilization, single node failure, underutilized resources, and high end-to-end delay. Blockchain and Software-Defined Networking (SDN) are growing technologies to create a secure system and to ensure safe network connectivity. Blockchain technology offers a strong and trustworthy foundation to deal with threats and problems, including safety, privacy, adaptability, scalability, and security. However, the integration of blockchain with SDN is still in the implementation phase, which provides an efficient resource allocation and reduced latency that can overcome the issues of industrial IoT networks. We propose an energy-efficient blockchain-integrated software-defined networking architecture for Industrial IoT (IIoT) to overcome these challenges. We present a framework for implementing decentralized blockchain integrated with SDN for IIoT applications to achieve efficient energy utilization and cluster-head selection. Additionally, the blockchain-enabled distributed ledger ensures data consistency throughout the SDN controller network and keeps a record of the nodes enforced in the controller. The simulation result shows that the proposed model provides the best energy consumption, end-to-end latency, and overall throughput compared to the existing works.

RESULTS OF THE EXPERIMENTAL STUDY OF THE FLOW FIELD OF A STATIONARY AIR FLOW DURING THE OPERATION OF A FOUR-BLADE BIDARRIEUS-1 TURBINE

There are a great variety of wind turbine constructions but by their principle of operation they are divided into three main types -sail (Savoniuswind power unit), propeller and airfoils (Darrieus wind turbine). At present, propeller-type wind-turbines are the most widely spread. They are produced on a commercial level in many countries. Other conditions being equal, the power produced by wind power unit (WPU) is proportional to the area being swept around by a wind wheel. Therefore, Megawatt propeller-type wind turbines have blades with the length of 40 and more meters. Only aircraft works with a highly-qualified personnel and corresponding equipment can produce such long blades of a specific shape. Of high interest have become airfoil wind turbines (Darrieus WPU) lately. They are of a simpler construction and have a quite high wind power utilization factor (ξ=0.45). In spite of the fact that this is a good index of WPU efficiency, the workers of al-Farabi Kazakh National University have developed a new version of a wind turbine which allows increasing 1.3-1.6 times the value of this coefficient. This apparatus is named a Bidarrieusunit. This paper presents the description of a Bidarrieusunit, the principle of its operation and the possibility of increasing the wind power utilization factor. Also, the results of testing an acting laboratory model in an aerodynamic tunnel

A novel methodology to manufacture complex metallic sudden overhangs in weld-deposition based additive manufacturing

PurposeAmongst various additive manufacturing (AM) techniques for realizing the complex metallic objects, weld-deposition (arc)-based directed energy AM technique is attaining more focus over commercially available powder bed fusion techniques. This is because of the capability of high deposition rates, high power and material utilization, simpler setup and less initial investment of arc-based AM. Nevertheless, realization of sudden overhanging features through arc-based weld-deposition techniques is still a challenging task because of the necessity of support structures. This paper aims to describe a novel methodology for producing complex metallic objects with sudden overhangs without using supports.Design/methodology/approachThe realization of complex metallic objects with sudden overhangs (without using supports) is possible by reorienting the workpiece and/or deposition head at every instance using higher order kinematics (5-axis setup) to make sure the overhanging feature is in line to the deposition direction.FindingsIn the absence of universally applicable support mechanism, deposition of overhanging features remains one of the main challenges in AM. A separate support structure is often necessary for depositing the overhanging features. Small overhang features are usually possible by a little overextension from the previous layer. Nevertheless, deposition of large gradually varying overhangs and sudden overhangs with complex features without support structures is a challenging task in any AM process. This demands higher order kinematics which calls for inclined and/or orthogonal slicing and area filling.Originality/valueThe unique aspect of this paper is the identification of sudden overhang feature from a tessellated computer-aided design (.stl) file and generates an orthogonal tool path for deposition for sudden overhangs. An in-house MATLAB routine has been developed and presented for performing the same. This methodology helps in realization of sudden overhangs without use of supports. To validate proposed technique, various illustrative case studies have been taken up for deposition.

Energy-Efficient Node Localization Algorithm Based on Gauss-Newton Method and Grey Wolf Optimization Algorithm

Node localization process is a crucial prerequisite in the area of Wireless Sensor Networks (WSNs). The algorithms for node localization process can either range-based or range-free. Range-free algorithms are preferred over range-based ones due to their cost-effectiveness. DV-Hop along with its variants is normally well-liked range-free algorithm because of its straightforwardness, scalability and distributed nature, but it has some disadvantages such as poor accuracy and high-power utilization. To deal with these limitations, this paper introduces an algorithm, called GWOGN-LA. GWOGN-LA improves accuracy by applying Grey-Wolf Optimization and Gauss-Newton method. The proposed algorithm restricts the forwarding of packets in order to limit energy consumption. Simulation results show that given proposal outperforms other state-of-art algorithms in terms of accuracy and power consumption.

Random forest based power sustainability and cost optimization in smart grid

Abstract Presently power control and management play a vigorous role in information technology and power management. Instead of non-renewable power manufacturing, renewable power manufacturing is preferred by every organization for controlling resource consumption, price reduction and efficient power management. Smart grid efficiently satisfies these requirements with the integration of machine learning algorithms. Machine learning algorithms are used in a smart grid for power requirement prediction, power distribution, failure identification etc. The proposed Random Forest-based smart grid system classifies the power grid into different zones like high and low power utilization. The power zones are divided into number of sub-zones and map to random forest branches. The sub-zone and branch mapping process used to identify the quantity of power utilized and the non-utilized in a zone. The non-utilized power quantity and location of power availabilities are identified and distributed the required quantity of power to the requester in a minimal response time and price. The priority power scheduling algorithm collect request from consumer and send the request to producer based on priority. The producer analysed the requester existing power utilization quantity and availability of power for scheduling the power distribution to the requester based on priority. The proposed Random Forest based sustainability and price optimization technique in smart grid experimental results are compared to existing machine learning techniques like SVM, KNN and NB. The proposed random forest-based identification technique identifies the exact location of the power availability, which takes minimal processing time and quick responses to the requestor. Additionally, the smart meter based smart grid technique identifies the faults in short time duration than the conventional energy management technique is also proven in the experimental results.

A Generic Theory for Design of Efficient Three-Stage Doherty Power Amplifiers

An analytical load—pull-based design methodology for three-stage Doherty power amplifiers (PAs) is presented and demonstrated. A compact output combiner network, together with the input phase delays, is derived directly from transistor load—pull data and the design requirements. The technique opens up a new design space for three-stage Doherty PAs with reconfigurable high-efficiency power back-off levels. The method is designed to enable high transistor power utilization by maintaining full voltage and current swings of the main and auxiliary amplifier cells. Therefore, a wide efficiency enhancement range can be achieved also with symmetrical devices. As a proof of concept, a 2.14-GHz 30-W three-stage Doherty PA with identical gallium nitride (GaN) HEMT active devices is designed, fabricated, and characterized. The prototype PA is able to linearly reproduce 20-MHz long-term evolution signals with 8.5- and 11.5-dB peak-to-average power-ratio (PAPR), providing average efficiencies of 56.6% and 46.8% at an average output power level of 36.8 and 33.8 dBm, respectively. Moreover, an average efficiency as high as 54.5% and an average output power of 36.3 dBm have been measured at an adjacent power leakage ratio of −45.7 dBc for a 100-MHz signal with 8.5 dB of PAPR, after applying digital predistortion linearization.

An improved switched‐ladder bidirectional multilevel inverter: Topology, operating principle, and implementation

AbstractMulti‐level inverters (MLIs) for medium or high power and voltage utilization have acceptable application in industry and are utilized commercially. The performance of MLIs is considerably preferable to traditional two‐level inverters due to their negligible harmonic content, small filter size, utilization of lower‐rated voltage devices, low electromagnetic interference (EMI), and so on. However, in the face of these many advantages, few disadvantages can be expressed such as more device count and a sophisticated control strategy. This paper presents an improved switched‐ladder topology to enhance the performance of multi‐level inverters by improving the above drawbacks. Compared to existing inverter topologies, the proposed extendable diode‐containing bidirectional structure requires fewer switches and driver circuits. The proposed topology is compared with other similar topologies, and its superiority is examined. Fundamental switching frequency modulation technique is utilized to obtain high‐quality output voltage waveforms with lower harmonic contents and reduced switching losses. This converter, despite the use of diodes, can supply the low power factor inductive‐resistive loads, bidirectionally. To demonstrate the performance of the proposed topology, in addition to simulation with the nearest level modulation technique, a prototype of the proposed structure has been implemented and tested. The results display the proper performance of the proposed topology in the real‐time environment.

Design of low power RF CMOS power amplifier structure with an optimal linear gain controller for future wireless communication

A power amplifier is a two-pair terminal gadget that creates a measured reflection of the input current at the high-resistance output terminal. Which holds the output current permanently regardless of loading? The significant elements affecting the presentation of a superior power amplifier are the amount of operation, and the amount of bandwidth, output resistance, and the minimum voltage drop required at both the input and output port terminal of the power amplifier circuits. To defeat those issues, low power RF CMOS PA is proposed with an optimal linear gain controller, which is reasonable for future wireless communication broadband applications. Bandwidth, high power-added efficiency, power utilization, and linearity, are focused on the proposed design. Fundamental commitments are summed up as follows. Here, an ideal linear gain controller plays out a completely differential CS arrangement of the cascade semiconductor gate contains an inductor, which is combined between the cascade semiconductor gate and opponent cascade semiconductor sources, it enhances voltage gain and improves the linearity. The XOR- based frequency multiplier removes the passive components. A computerized pre-warping method is additionally used to remunerate the discrete force gain variations and beats the tradeoffs between power proficiency and linearity. The proposed PA implemented the 0.13-μm standard RF CMOS method. The presentation of the propounded PA is contrasted with the current PAs with performance metrics are power-added efficiency (PAE), linearity, voltage gain, and power gain. So, it is being examined with a 256-QAM WLAN 802.11ac signal source.

Evaluation and Prediction of Wind Power Utilization Efficiency Based on Super-SBM and LSTM Models: A Case Study of 30 Provinces in China

Although China’s wind industry has made great progress in recent years, the wind abandonment phenomenon caused by the unbalanced development of regional wind power is still prominent. It is particularly important for the scientific development of wind power to accurately measure the utilization efficiency of wind power and understand its regional differences in China. This study establishes the improved super-efficiency slack-based measure (Super-SBM) model and long short-term memory (LSTM) network models, systematically and comprehensively measures and predicts the wind power utilization efficiency of 30 regions in China from 2013 to 2020, and explores regional differences in wind power utilization efficiency. Our results show the following: (1) China’s overall wind power utilization efficiency is relatively low but has been on a steady upward trend since 2013. (2) Regional differences are obvious, showing that the spatial distribution pattern of wind power utilization efficiency is greatest in Northeast China, followed by North China, East China, South China, Northwest China, and Central China. The “Three-North” region with abundant wind energy resources has relatively high wind power utilization efficiency and exhibits a good development trend. East China, South China, and Central China, where wind energy resources are relatively poor, have low wind power utilization efficiency, and their development trends are not stable and are more prone to change. (3) The utilization efficiency of wind power in coastal areas is generally better than that in inland areas. There are also differences among the thirty Chinese regions studied. Inner Mongolia and Shandong have achieved real efficiency in wind power utilization efficiency, with optimal allocation of input and output, and a good development trend. The other 28 regions have varying degrees of inefficiency, and there is still room for improvement.

Adaptation of counters redundant bits with the provision of dual supply and modified clock gating to favour of low power in VLS

The utilization of usual supply voltage and clock for repetitive state transistors in digital circuits is a fundamental driver for high power utilization. Most significant bit states of the counter stay longer than the least significant bit states and it has some repetitive states. To limit the supply voltage and stop the clock for MSB Flip Flop (FF) transistor, our method uses Control Combinational Logic, Voltage selector and Modified Integrated Clock Gating blocks. The LSB transistor always have a supply voltage of 1.2V and succession of the clock, while MSB transistor gets just 480mV and the clock will be stopped by the this technique. Bring down the supply voltage and quit the clock for redundant states either 0 or 1 in MSB. Meantime supply 1.2V and clock for state changes over from one state to next state. The experimental simulation was done in 45nm CMOS technology using Cadence virtuoso indicates that this asynchronous counter achieves a power savings of 23.57% and the same modified technique when applied to the counters with transmission-gate FF, hybrid-latch FF and sense amplifier FF will have more than 40% power savings and the technique applied in some benchmark circuits will have more than 22% power savings than existing techniques.

Bandwidth Enhancement of Frequency Dispersive Doherty Power Amplifier

This letter presents a modified Doherty power amplifier (DPA) combining network with wide bandwidth (BW) and high power utilization factor (PUF). For the first time, the impact of the excessive phase dispersion of matching networks on the performance of conventional broadband DPA is analytically revealed. For dispersion compensation, an optimized adaptive combining load is introduced to enhance the achievable DPA BW and PUF. For verification, a 42-dBm equal-cell DPA is prototyped to cover 1.4–2.55 GHz. Measurement results indicate that, over the prescribed frequency range, a PUF of over 0.95, back-off efficiency (6 dB) of 48%–58%, and saturation efficiency of 62%–74% can be achieved. Moreover, under WCDMA excitation, the adjacent channel leakage ratio (ACLR) was found to be better than −32 dBc with average efficiency of over 45% without applying digital predistortion techniques.

Wind Power Pricing Game Strategy under the China’s Market Trading Mechanism

Wind power has become the main power generation method in China’s clean energy power generation because of its clean and high efficiency, as well as its high power utilization rate. The research on its pricing mechanism has also become the main research focus of the wind power industry. However, wind power pricing is still at the stage of price benchmarking and no market mechanism has been introduced in China. There are still much research on the pricing mechanism of wind power for us to study. In this paper, the Kernel method is used to distribute wind power income. On the basis of the distribution result, considering the contract execution risk of wind power, cooperative game theory and the Shapley value method are used to redistribute the revenue of wind power connected to power grid. Based on the characteristics of alliance members, ANP (Analytic Network Process) was used to modify the apportioned benefits to obtain the benefit distribution method that was more in line with the interest demands of members, and an example was analyzed. The wind power pricing model based on the cooperative game established in this paper can guarantee the smooth operation of the alliance, reach the pareto optimum, and improve the activity of the wind power market. It will effectively shorten the negotiation time, and reduce the transaction cost and the uncertainty of the wind power transaction.

Low-power design-for-test implementation on phase-locked loop design

Low-power design for test is the need of the hour for any system-on-chip designer. The low-power design techniques have been a major challenge to both the designer as well as the testing engineer. With so many advancements in low-power technology in the phase of register transfer logic design, functional verification, register transfer logic and physical synthesis and physical design. Design for test is not an exception to this. The low-power design-for-test techniques can be applied at various levels of the design-for-test flow as in the scan insertion stage, automatic test pattern generation simulations stage, testing stage, and so on. Some of the reasons for the high-power utilization in the design-for-test phase can be due to the external circuitry being inserted during the design phase and not used in the functional mode. The complete circuit will be active in the test mode only. In this paper, the focus will be primarily on reducing the power during the automatic test pattern generation scan synthesis phase. All the scan flops are connected by a common scan clock with a fixed frequency. The intention of this study is to divide the clock frequency by half and make sure that the power is reduced without affecting any timing violations. Since the scan clock frequency is low, it can be further divided to ensure that power is reduced without affecting the testing process of the chip.

A Novel Multi-Objective Efficient Offloading Decision Framework in Cloud Computing for Mobile Computing Applications

Mobile cloud computing is the emerging paradigm to improve mobile device computation issues using cloud resources. Computation offloading is an efficient way of transferring certain tasks from mobile devices to the cloud. The computationally intensive task of the mobile application executes on the remote cloud. In computational offloading, the decision making plays a vital role to decide whether a task to be offloaded to the cloud or to execute in the local side. The existing research focused either on the offloading part of the cloud side or the context of mobile devices. However, this paper considered both the cloud side and the mobiles side to make the efficient decision offloading decision. This paper proposes a novel multi-objective efficient offloading decision framework for supporting computational offloading based on the mobile applications’ complexity and the context of mobile devices. The main purpose of this framework is to improve the mobile devices, which executes the high computational task that consumes the high battery power and CPU utilization. The proposed framework dynamically explores and decides the optimal cloud by using the enhanced particle swarm optimization algorithm. Moreover, this paper reduces the battery power consumption, virtual machine cost and makespan of the task for providing the quality of services.

Efficient FPGA‐based VLSI architecture for detecting R‐peaks in electrocardiogram signal by combining Shannon energy with Hilbert transform

Electrocardiogram (ECG) is a critical application in light of R-peak detection. The R-peaks are impacted by some QRS complex and noises in the current method. Basic testability, snappier execution, and confirmation choices are accomplished by the utilization of the field programmable gate array (FPGA). But, FPGA execution gives less accuracy. To battle execution trouble, another R-peak detector is proposed and relying upon the propelled peak finding logic, which incorporates a Bandpass filter and first-order differentiation process, which are done in the primary phase of the strategy. The noises in the input ECG signal are decreased in the first stage. In the subsequent stage, the smooth Shannon energy envelope (SEE) is acquired by utilizing SEE extraction and the zero phases filtering process. The false R peak is stifled by proposing a Hilbert transform (HT) in the third stage. The HT requires more hardware space and high-power utilization in the current technique. Due to this reason, Real valued Fast Fourier Transform (RFFT) and Inverse RFFT (IRFFT) techniques are proposed in the HT. In the fourth stage, R-peak acknowledgment is evaluated using Massachusetts Institute of Technology, Beth Israel Hospital (MIT-BIH) arrhythmia database and produced the average accuracy of 99.86%, sensitivity of 99.95% and the positive predictivity of 99.90%.