《International Journal of Hydrogen Energy》2023,48(73):28445-28452

Hydrogen is an energy carrier which can be processed by high pressure compressor and they can be transported, stored and converted to electricity for later use. This paper proposes a hydrogen compression model development and modeling of hydrogen transportation between two tanks using MATLAB software version 22. The proposed model provides amount of hydrogen required in volumes (m³) and compressor power required in (KW) for compressor speed of 500 rad/s, 1000 rad/s and 1500 rad/s. This model provides hydrogen volume of 1 m³ and 10 KW compressor power requirement at 500 rad/s compressor speed. For compressor speed of 1000 rad/s, the proposed model provides hydrogen volume of 10 m³and 20 KW compressor power requirements and for 1500 rad/s this model provides volume of 30 m³and 30 KW compressor power requirements which indicates that the increase in compressor speed increases hydrogen volume generated and increase the power requirement also. For maintaining compressor speed at desired value, a PID (Proportional + Integral + Derivative) controller has been designed and the results were compared with Proportional (P), PI (Proportional + Integral), and PD (Proportional + Derivative) controllers. PID controller performance can be measured using the parameters delay time and settling time. Low values of settling time and delay time indicate the better performance of PID controller. P controller achieves the desired compressor speed with delay time of 228 ms; settling time of 1250 s. PI controller achieves the desired compressor speed with delay time of 210 ms, settling time of 1210 s. PD controller achieves the desired compressor speed with delay time of 185 ms, settling time of 1280 s. PID controller provides better speed regulation with low delay time of 110 ms and settling time of 1120 s when compared with P, PI, PD controllers. From the simulation results it is observed that PID controller can be a good option for slow process like hydrogen gas flow through pipeline for effective speed regulation.  相似文献   

    

《Microprocessors and Microsystems》2020

Dynamic power management strategies are generally used to achieve efficient power consumption of battery operated computer systems. Such computer systems usually integrate a number of built-in power-management policies. These policies are generally integrated into device drivers and cannot be changed. This paper addresses the problem of adaptive dynamic power management of a battery operated computer with self-power managed components. The power management task is split into Component Power Manager (CPM) and Global Power Manager (GPM). The CPM is the local-level policy that is pre-defined and can't change. The GPM cannot overwrite the CPM policy. A Service Flow Controller (SFC) is incorporated to control the service request generation for a specific component. The GPM uses model free reinforcement learning to adequately guide SFC actions. Moreover, the GPM implements Reinforcement learning based battery power management aiming at optimizing the battery's State of Charge (SoC) and improving its lifetime. This is performed by letting the GPM adapt the system quality of services to the actual battery SoC. Experiments on measured data traces confirmed the effectiveness of the proposed approach. Up to 57.2% of maximum SoC savings are obtained while good performance levels are maintained. Compared to prior reference studies, the proposed approach is model free, event driven, adapts to non-stationary workloads, considers multiple types of user applications, models the battery nonlinear characteristics, can handle SoC degradation and performance at the same time, and is capable to achieve deep and wide SoC degradation/performance tradeoff curves.  相似文献   

    

《Microprocessors and Microsystems》2020

Power Distribution systems are one of the most critical links between utility and utility customer. Control of power loss in distribution systems are very much essential considering the economical aspects. Reconfiguration, Capacitor Placement and Phase Balancing are the different methods practiced for power loss reduction. Due to the unbalanced nature of the distribution system, phase balancing is considered as the effective one amongst the above mentioned three methods. Unbalanced feeders not only increase power losses and the risk of overload situations, but they also affect power quality and electricity price. A severely unbalanced circuit can result in excessive voltage drops on the heavily phase. Even a feeder system is designed as a balanced feeder based on the given load data, load prediction errors and unbalanced load growth will induce feeder imbalance. Phase swapping is a direct and effective way to balance a feeder in terms of phases. It has been practiced by engineers based on their previous experiences, and trial and error for phase balancing. In this paper, a phase swapping algorithm based on hybrid Fuzzy-Flower Pollination Algorithm (FFPA) has been developed to minimize the phase current deviation amongst the phases. Flower Pollination Algorithm is used to optimize the fitness value and fuzzy used to format the fitness function integrating multi-objectives. The validation of the proposed algorithm is done through two standard test cases and simulation results are compared with literature.  相似文献   

    

Krishnamoorthy  D.  Nagoor Meeran  M.  Prakasam  A.  Thangaraju  D. 《Journal of Materials Science: Materials in Electronics》2022,33(3):1280-1292

Journal of Materials Science: Materials in Electronics - This study describes the flexible DSSC devices based on efficient TiS2/Reduced Graphene Oxide (TiS2/RGO) hybrid photoanodes that have been...  相似文献   

    

A. Kavitha  Koppala Guravaiah  R. Leela Velusamy  S. Suseela  Dhilip Kumar V 《International Journal of Communication Systems》2023,36(8):e5467

Internet of Things (IoT) has got significant popularity among the researchers' community as they have been applied in numerous application domains. Most of the IoT applications are implemented with the help of wireless sensor networks (WSNs). These WSNs use different sensor nodes with a limited battery power supply. Hence, the energy of the sensor node is considered as one of the primary constraints of WSN. Besides, data communication in WSN dissipates more energy than processing the data. In most WSNs applications, the sensed data generated from the same location sensor nodes are identical or time-series/periodical data. This redundant data transmission leads to more energy consumption. To reduce the energy consumption, a data reduction strategy using neural adaptation phenomenon (DR-NAP) has been proposed to decrease the communication energy in routing data to the BS in WSN. The neural adaptation phenomenon has been utilized for designing a simple data reduction scheme to decrease the amount of data transmitted. In this way, the sensor node energy is saved and the lifetime of the network is enhanced. The proposed approach has been implanted in the existing gravitational search algorithm (GSA)-based clustered routing for WSN. The sensed data are transmitted to CH and BS using DR-NAP. Real sensor data from the Intel Berkeley Research lab have been used for conducting the experiments. The experiment results show 47.82% and 51.96% of improvement in network lifetime when compared with GSA-based clustered routing and clustering scheme using Canada Geese Migration Principle (CS-CGMP) for routing, respectively.  相似文献   

    

《International Journal of Hydrogen Energy》2020,45(10):5881-5889

Biohydrogen production from seagrass (SG) has gained much attention due to their chemical composition (carbohydrate rich biomass). In this study, an attempt was made to enhance the biohydrogen production from sea grass through novel ozone coupled rotor-stator homogenization (ORSH). The efficiency of the homogenization pretreatment was evaluated in terms of seagrass lysis and biohydrogen generation. Initially, sea grass was subjected to rotor-stator homogenization (RSH) to optimize its power input (5.4–19.1 W) and energy spent (0–1285 kJ/kg TS). RSH consumes specific energy of 510 kJ/kg TS to achieve seagrass lysis of 10.45%, whereas ORSH achieved 23.7% of seagrass lysis at less energy (212.4 kJ/kg TS) input. The outcome of the present study reveals ORSH reduced 58.3% of energy input and increased 55.9% of SG lysis when compared with RSH. Hence, a considerable amount of energy could be saved through this combinative pretreatment. Biohydrogenesis was done to evaluate and compare the biohydrogen production potential of ORSH sample. Higher ultimate biohydrogen production was achieved by ORSH (90.7 mL/g COD) than RSH (39.6 mL/g COD). A higher energy ratio of 1.17 could be achieved through ORSH.  相似文献   

    

《Computers & chemistry》1994,18(4):413-417

This paper presents a software tool for determining the vibrational energy levels and the vibronic structure of electronic spectra in molecules showing one, two or more large amplitude motions. The program, ROVI, uses the potential functions and the kinetic terms for each electronic state in the construction of the hamiltonian matrix. The hamiltonian is solved variationally in a free rotor basis to obtain the energy levels and the wavefunctions. In addition, the temperature and the transition dipole moment are used for the calculation of the vibronic structure of the electronic spectrum. ROVI simulates the transitions as vertical lines or by a superposition of lorentzian functions. The program is used to illustrate the change in the vibronic structure of the S₀ → T₁ electronic spectrum of acetaldehyde with the temperature.  相似文献   

    

《Materials Science in Semiconductor Processing》2015

SnS quantum dots (QDs) with size of 8 nm were synthesized by an in-situ room temperature solution chemical reaction process. Stannous chloride, as Sn precursor, was coated on the TiO₂ photo-anodes to form a solid precursor film. Ammonium sulfide was dissolved into ethanol to form anionic reaction solution. SnS quantum dots were generated by immersing the Sn-coated TiO₂ photo-anodes into the anionic solution. The structure, morphology and optical absorption properties of the SnS/TiO₂ photoanodes were investigated by means of XRD, SEM, TEM and UV–vis measurements. The photovoltaic properties of the SnS QDs sensitized TiO₂ solar cells were optimized by changing the number of deposition cycles of the SnS QDs. It turns out that the SnS/TiO₂ solar cell with 20 deposition cycles exhibited the best photovoltaic performance with an open-circuit voltage V_oc of 510 mV, a short-circuit current density Jsc of 2.41 mA, a fill factor FF of 0.49 and a power conversion efficiency η of 0.61% under AM 1.5 illumination. This result is interpreted in terms of minimization of the charge transfer resistance. The performance will drop for further deposition because the charge transfer resistance will increase due to QDs agglomeration.  相似文献   

Enhancement in the optical and magnetic properties of ZnO:Co implanted by Gd3+ nanoparticles     

T. Thangeeswari  M. Priya  J. Velmurugan 《Journal of Materials Science: Materials in Electronics》2015,26(4):2436-2444

  相似文献   

    

Riya Kumarasamy Santhanaraj  Surendran Rajendran  Carlos Andres Tavera Romero  Sadish Sendil Murugaraj 《计算机系统科学与工程》2023,45(2):1561-1576

Wireless Sensor Networks (WSNs) are a major element of Internet of Things (IoT) networks which offer seamless sensing and wireless connectivity. Disaster management in smart cities can be considered as a safety critical application. Therefore, it becomes essential in ensuring network accessibility by improving the lifetime of IoT assisted WSN. Clustering and multihop routing are considered beneficial solutions to accomplish energy efficiency in IoT networks. This article designs an IoT enabled energy aware metaheuristic clustering with routing protocol for real time disaster management (EAMCR-RTDM). The proposed EAMCR-RTDM technique mainly intends to manage the energy utilization of nodes with the consideration of the features of the disaster region. To achieve this, EAMCR-RTDM technique primarily designs a yellow saddle goatfish based clustering (YSGF-C) technique to elect cluster heads (CHs) and organize clusters. In addition, enhanced cockroach swarm optimization (ECSO) based multihop routing (ECSO-MHR) approach was derived for optimal route selection. The YSGF-C and ECSO-MHR techniques compute fitness functions using different input variables for achieving improved energy efficiency and network lifetime. The design of YSGF-C and ECSO-MHR techniques for disaster management in IoT networks shows the novelty of the work. For examining the improved outcomes of the EAMCR-RTDM system, a wide range of simulations were performed and the extensive results are assessed in terms of different measures. The comparative outcomes highlighted the enhanced outcomes of the EAMCR-RTDM algorithm over the existing approaches.  相似文献